Patent Application
20240068042
BRCA1 (BReast CAncer gene 1) and BRCA2 (BReast CAncer gene 2) encode proteins that help repair damaged DNA. Variants of these BRCA1/BRCA2 genes have been associated with increased risk of several cancers, including breast cancer and ovarian cancer. About 55%-72% of women who inherit a harmful BRCA1 variant and about 45%-69% of women who inherit a harmful BRCA2 variant will develop breast cancer by 70-80 years of age; and about 39%-44% of women who inherit a harmful BRCA1 variant and about 11%-17% of women who inherit a harmful BRCA2 variant will develop ovarian cancer by 70-80 years of age.
Following surgery to remove a primary cancer, platinum-based drugs such as cisplatin, carboplatin and oxaliplatin are often prescribed as a first-line chemotherapy. While they are effective in some patients, their use is limited by their severe, dose-limiting side effects.
The present disclosure provides, in some embodiments, methods to guide the selection of cancer (e.g., breast or ovarian cancer) patients who will likely be ‘good responders’ or ‘poor responders’ to treatment with a platinum-based chemotherapy agent. Such methods may limit the number of ‘poor responders’ who are unnecessarily exposed to the harmful side-effects of platinum-based agents. The experimental data described herein demonstrate that a BRCA1 and BRCA2 mutational status accompanied by a certain immune signature can be a predictor of how a particular population of patients will respond to platinum-based chemotherapy.
As described in the Examples below, the present disclosure provides a ‘decision tree’ for predicting patient response to platinum-based chemotherapy. By considering BRCA1/2 pathogenic mutational status and the expression of an immune signature in BRCA1/2 wild-type tumors, the methods provided herein can be used to more accurately predict chemo-responsiveness than by using BRCA1/2 mutational status alone or homologous recombination deficiency (HRD) scores. For example, a response state was developed based on the presence of BRCA1/2 pathogenic mutations in a tumor and, in a subset of patients having a BRCA1/2 wild-type tumor, on the strength of a M1 macrophage immune signature. Based on this decision tree, each tumor (and thus each patient) was given an assessment of ‘good’ or ‘poor’ (
The same cohorts were also stratified based on BRCA1/2 status alone. All modes of patient stratification were then compared to the actual clinical outcomes, using both log rank and COX proportional hazard ratio test statistics, to assess and quantify their predictive value. In each of the cohorts examined, the response outcomes predicted by the decision tree provided herein outperformed the predictive power of BRCA1/2 status alone, as indicated by lower hazard ratios and p-values (
The data provided herein support the hypothesis that ‘BRCAness status,’ and consequently HRD, are not good predictors of chemotherapeutic response per se, and that additional patient stratification taking into account how the BRCAness status is achieved in a cancer genome is a better predictor of patient responses. The data also highlight the relevance of BRCA1/2-based patient classification prior to assessing the potential role of immune infiltrates in guiding tumor responsiveness.
Some aspects of the present disclosure provide a method comprising: assaying a tumor sample from a subject for a wild-type BRCA1 and BRCA2 (BRCA1/2) gene mutational status; and assaying for an immune signature in the tumor sample identified as having a wild-type BRCA1/2 gene mutational status, wherein the immune signature is above or below a threshold level.
In some embodiments, the method further comprises selecting the subject for a therapy with a platinum-based agent if the immune signature is above the threshold level.
In some embodiments, the method further comprises selecting the subject for no therapy or a therapy other than the combination therapy if the immune signature is below a threshold level.
Other aspects of the present disclosure provide a method comprising: assaying a tumor sample from a subject for a BRCA1/2 gene mutational status selected from wild-type and mutated; optionally assaying the tumor sample identified as having a wild-type BRCA1/2 gene mutational status for an immune signature, wherein the immune signature is above or below a threshold level; and (a) selecting the subject for a therapy with a platinum-based agent if (i) the tumor sample has a wild-type BRCA1/2 gene mutational status and an immune signature above the threshold level, or (ii) the tumor has a mutated BRCA1/2 gene mutational status, or (b) selecting the subject for no therapy or a therapy other than a therapy with a platinum-based agent if the tumor sample has a wild-type BRCA1/2 gene mutational status and an immune signature below the threshold level.
Yet other aspects of the present disclosure provide a method comprising: assaying a tumor sample from a subject for a BRCA1/2 gene mutational status selected from wild-type and mutated; optionally assaying the tumor sample identified as having a wild-type BRCA1/2 gene mutational status for an immune signature, wherein the immune signature is above or below a threshold level; designating the subject as a good responder or a poor responder to a therapy with a platinum-based agent based on the BRCA1/2 gene mutational status of the tumor sample.
In some embodiments, the subject is designated as a good responder if the tumor sample has a mutated BRCA1/2 gene mutational status.
In some embodiments, the subject is designated as a good responder if the tumor sample has a wild-type BRCA1/2 gene mutational status and the immune signature is above the threshold level.
In some embodiments, the subject is designated as a poor responder if the tumor sample has a wild-type BRCA1/2 gene mutational status and the immune signature is below the threshold level.
In some embodiments, the method further comprises selecting the subject for a therapy with a platinum-based agent if the subject is a good responder.
In some embodiments, the immune signature is a M1 macrophage immune signature generated using an algorithm capable of estimating abundances of member cell types in a mixed cell population using gene expression data, optionally wherein the algorithm is CIBERSORT.
In some embodiments, the immune signature is an immune cell-specific enrichment score generated using an algorithm capable of calculating separate enrichment scores for each pairing of a sample and gene set, wherein each enrichment score represents the degree to which genes in a particular gene set are coordinately up-regulated or down-regulated within a sample, optionally wherein the algorithm is single sample Gene Set Enrichment Analysis (ssGSEA).
In some embodiments, the immune signature is an immune subtype assignment based on the TNBCtype classification system.
In some embodiments, the immune signature is based on the measurement of one or more immune gene set.
In some embodiments, the tumor sample is from a subject with breast cancer, optionally triple negative breast cancer (TNBC). In other embodiments, the tumor sample is from a subject with ovarian carcinoma (OV).
In some embodiments, the platinum-based agent is selected from the group consisting of oxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin.
In some embodiments, the therapy is a combination therapy that comprises at least one agent in addition to the platinum-based agent.
In some embodiments, the combination therapy comprises a taxane.
In some embodiments, the taxane is selected from the group consisting of paclitaxel, docetaxel, and cabazitaxel. In other embodiments, the combination therapy comprises cisplatin or carboplatin. In some embodiments, the combination therapy comprises docetaxel.
Other aspects of the present disclosure provide a method comprising assaying a primary tumor sample for promoter methylation status of a wild-type BRCA1 gene from a subject prior to the subject receiving a therapy; and (a) selecting the subject for a therapy with a platinum-based agent if the tumor sample has a promoter methylation status of fully methylated, or (b) selecting the subject for an alternative therapy without a platinum-based agent or no therapy if the tumor sample has a promoter methylation status of partially methylated or unmethylated.
Other aspects of the present disclosure provide a method comprising assaying a recurrent tumor sample for promoter methylation status of a wild-type BRCA1 gene from a subject, wherein a primary tumor sample from the subject was previously assayed for promoter methylation status of a wild-type BRCA1 gene, and wherein the promoter methylation status of the primary tumor was fully methylated; and (a) selecting the subject for a therapy with a platinum-based agent if the recurrent tumor sample has a promoter methylation status of fully methylated, or (b) selecting the subject for an alternative therapy without a platinum-based agent if the recurrent tumor sample has a promoter methylation status of partially methylated or unmethylated.
In some embodiments, the method further comprises assaying for expression of a wild-type BRCA1 gene.
In some embodiments, the promoter methylation status is assayed by Methylation-Specific PCR (MSP), Methylation-Specific Digital Droplet PCR (MS-ddPCR), and/or Next Generation Sequencing of bisulfite converted DNA amplicons.
In some embodiments, the tumor sample is from a subject with breast cancer, optionally triple negative breast cancer (TNBC).
In some embodiments, the tumor sample is from a subject with ovarian carcinoma (OV).
In some embodiments, the platinum-based agent is selected from the group consisting of oxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin.
In some embodiments, the therapy is a combination therapy that comprises at least one agent in addition to the platinum-based agent.
In some embodiments, the combination therapy comprises a taxane.
In some embodiments, the taxane is selected from the group consisting of paclitaxel, docetaxel, and cabazitaxel.
In some embodiments, the combination therapy comprises cisplatin or carboplatin.
In some embodiments, the combination therapy comprises docetaxel.
The present disclosure provides, in some aspects, methods for predicting a cancer (e.g., breast cancer or ovarian cancer) patient's response to platinum-based chemotherapy. The experimental data provided herein was generated using (a) a detailed analysis of whole genome sequence (WGS) data, (b) treatment response studies from three cohorts of patients having triple negative breast cancer (TNBC) or ovarian cancer who were treated with chemotherapeutic agents containing a platinum-based compound, and (c) TNBC patient-derived xenograft (PDX) models, collectively demonstrating that BRCA1 and BRCA2 (BRCA1/2) pathogenic mutations in certain patient populations are associated with positive responses to platinum-based chemotherapy. The data provided herein also suggests that the previously used classification of tandem duplicator phenotype (TDP) score or TDP type does not predict for improved chemotherapeutic response and further suggests that the general phenotype of genomic instability as measured by any instability score such as LOH-based HRD metrics may be insufficient to predict for therapeutic response. The data provided herein highlights a clear differential effect on therapeutic response between tumors harboring BRCA1 mutations versus those with reduced BRCA1 expression through promoter methylation, even though the two forms of BRCA1 alterations results in identical genomic scarring. The present disclosure provides data supporting an association between immune score and therapeutic response in TNBC and ovarian cancer appear to be most predictive in the BRCA1/2 wildtype subgroup. Further, the present disclosure provides data provided supporting full BRCA1 promoter methylation in primary and/or recurrent tumors is predictive of positive therapeutic response to platinum-based agents.
Breast cancer early onset gene 1 (BRCA1) is a tumor suppressor gene located on chromosome 17q21 that encodes a protein composed of 1863 amino acid residues. BRCA1 regulates transcription, DNA double-strand breaks, and recombination. Breast cancer early onset gene 2 (BRCA2) is a tumor suppressor gene located on chromosome 13q12 that encodes a protein composed of 3418 amino acids. Both BRCA1 and BRCA2 are homology-directed repair (HDR) genes and are associated with predispositions to breast, ovarian, and, at lower frequency, prostate, pancreatic, and other cancers. As used herein, the term BRCA1/2 refers to BRCA1 and BRCA2.
The methods described herein, in some embodiments, comprise assaying a tumor sample for a BRCA1/2 gene mutational status. The BRCA1/2 gene mutational status of a tumor sample corresponds to the BRCA1/2 gene mutational status of the BRCA1/2 genes in the tumor sample. The term BRCA1/2 gene mutational status refers to one of two BRCA1/2 genotypes: wild-type BRCA1/2 and mutated BRCA1/2. BRCA1/2 gene mutational status can be determined by any method used for genotyping and/or method for determining epigenetic changes (e.g., methylation) in a gene such as, for example, Sanger sequencing/multiplex ligation-dependent probe amplification (MLPA) and next-generation sequencing (NGS). The term wild-type BRCA1/2 gene mutational status, as used herein, is assigned to BRCA1/2 genes that encode functional proteins (e.g., protein activities capable of regulating transcription, DNA double-strand breaks, and/or recombination). It should be understood that BRCA1/2 genes assigned to a wild-type BRCA1/2 ‘mutational status’ need not be wild-type genes in the conventional sense but may include a (at least one) modification (e.g., missense mutation and/or single nucleotide polymorphism), relative to the BRCA1 and BRCA2 genes having, for example, the nucleic acid sequence listed in the Ensemble database at ENSG00000012048 and ENSG00000139618, respectively, provided the BRCA1/2 genes encode functional proteins.
In some embodiments, BRCA1/2 genes assigned to a wild-type BRCA1/2 mutational status encode proteins that exhibit a level of activity within 50% (e.g., within 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%) of the level of activity of a protein encoded by BRCA1/2 genes comprising the nucleic acid sequence listed in the Ensemble database at ENSG00000012048 and ENSG00000139618, respectively. BRCA1 protein activity may be measured using, for example, the transcription activation (TA) assay (Monteiro et al., 1998, incorporated by reference), the small colony phenotype assay (Coyneh et al., 2004, incorporated by reference), the rescue of radiation sensitivity assay (Scully et al., 1999, incorporated by reference), the ubiquitin ligase activity assay (Morris et al., 2006, incorporated by reference), or functional complementation assays, and PARP inhibitor sensitivity assay (Bouwman et al, 2013, incorporated by reference). Other BRCA1 functional assays known or later developed are also contemplated. BRCA2 protein activity may be measured using, for example, in vitro assays that measure (a) mitomycin C (MMC) sensitivity, (b) homologous recombination DNA repair and (c) centrosome amplification (Wu et al., 2005, incorporated by reference). Other BRCA2 functional assays known or later developed are also contemplated.
The term mutated BRCA1/2 gene mutational status, as used herein, is assigned to BRCA1/2 loss-of-function alleles. Loss-of-function alleles, as in known in the art, include complete loss-of-function alleles (alleles that do not encode a functional protein—also known as amorph or null alleles) as well as partial loss-of-function alleles (alleles that encode an incompletely functioning protein—also known as hypomorphs or leaky mutations). BRCA1/2 loss-of-function alleles may include any pathogenic or likely pathogenic mutation. A pathogenic mutation is any genetic alteration that increases a subject's susceptibility or predisposition to a certain disease or disorder, such as cancer (e.g., breast cancer or ovarian cancer). Some types of BRCA1/2 mutations are known in the art to be pathogenic. Other types of BRCA1/2 mutations, which are predicted by those in the art to be pathogenic, are termed “likely pathogenic” mutations. In some embodiments, BRCA1/2 mutations are classified as pathogenic or likely pathogenic based on a mutation database such as the ClinVar database (www.ncbi.nlm.nih.gov/clinvar/, incorporated by reference), and/or the ARUP BRCA database (https://arup.utah.edu/database/BRCA1, incorporated by reference). Other databases that may be used by a those skilled in the art to determine whether a mutation is pathogenic or likely pathogenic are also contemplated. In some embodiments, a tumor sample is assigned a mutated BRCA1/2 gene mutational status if the tumor sample comprises BRCA1/2 genes that have pathogenic or likely pathogenic mutations based on a mutation database described above or otherwise known in the art.
Pathogenic mutations may emerge in various forms including, but not limited to, nonsense mutations, frameshift mutations, missense mutations, short insertions/deletions, splice site mutations, stop codon read-through mutations and rearrangements). In some embodiments, BRCA1/2 pathogenic mutations include nonsense or missense mutations. In some embodiments, BRCA1/2 pathogenic mutations include mutations that result in a frameshift of the resulting amino acid sequence. In some embodiments, BRCA1/2 pathogenic mutations include mutations that result in short insertion/deletion sequences within the BRCA1/2 exon regions. In some embodiments, BRCA1/2 pathogenic mutations include mutations that result in changes to the splice site of the BRCA1/2 exons. In some embodiments, BRCA1/2 pathogenic mutations include mutations that result in premature stop codons. In some embodiments, BRCA1/2 pathogenic mutations may be a structural rearrangement of BRCA1/2 gene regions, such as a structural rearrangement that results in the loss or translocation of at least part of the BRCA1/2 gene coding region.
In some embodiments, BRCA1/2 genes assigned to a mutant BRCA1/2 mutational status encode proteins that exhibit a level of activity that is less than 50% (e.g., less than 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, or 5%) of the level of activity of a protein encoded by BRCA1/2 genes comprising the nucleic acid sequence listed in the Ensemble database at ENSG00000012048 and ENSG00000139618, respectively.
In some embodiments, BRCA1/2 genes assigned to a mutant BRCA1/2 mutational status encode nonfunctional proteins (no detectable function).
In some embodiments of the present disclosure, the BRCA1/2 gene mutational status of a tumor sample is from a subject with triple negative breast cancer (TNBC). In some embodiments of the present disclosure, the BRCA1/2 gene mutational status of a tumor sample is from a subject with ovarian carcinoma (OV).
The methods described herein, in some embodiments, comprise assaying a tumor sample for BRCA1 promoter methylation status. Promoter methylation is a form of epigenetic regulation wherein methyl groups added to DNA molecules may alter the activity of gene expression without altering the DNA sequence. In some embodiments, BRCA1 promoter methylation may act to repress gene transcription of the BRCA1 gene and decrease BRCA1 protein expression. In some embodiments, a decrease in BRCA1 promoter methylation may result in increased BRCA1 protein expression. In some embodiments, a tumor sample is assayed for BRCA1 promoter methylation status. In some embodiments, a tumor sample is assayed for both BRCA1 promoter methylation status and BRCA1 protein expression.
Promoter methylation may be measured or determined using a variety of methods known in the art, including but not limited to, Methylation-Specific PCR (MSP), Methylation-Specific Droplet Digital PCT (MS-ddPCR), and/or Next Generation Sequencing of bisulfite converted DNA amplicons. Other methods of quantifying promoter methylation known in the art are also contemplated herein.
The term BRCA1 promoter methylation status refers to the level of methylation of the DNA within the promoter region of the BRCA1 gene measured in a tumor sample from a subject (e.g., BRCA1 promoter methylation status can be fully methylated, partially methylated, or unmethylated). In some embodiments, the BRCA1 promoter methylation status of a primary or recurrent tumor from a subject may inform therapy selection.
In some embodiments, a primary tumor sample from a subject comprises a BRCA1 promoter methylation status that is fully methylated. In some embodiments, a subject may respond better to therapy with a platinum-based agent if a primary tumor sample from the subject has a promoter methylation status of fully methylated. In some embodiments, a subject may be selected for therapy with a platinum-based agent if a primary tumor sample from the subject has a promoter methylation status of fully methylated.
In some embodiments, a primary tumor sample from a subject comprises a BRCA1 promoter methylation status that is partially methylated or unmethylated. In some embodiments, a subject may respond better to an alternative therapy that does not include a platinum-based agent if a primary tumor sample from the subject has a promoter methylation status of partially methylated or unmethylated. In some embodiments, a subject may be selected for an alternative therapy that does not include a platinum-based agent if a primary tumor sample from the subject has a promoter methylation status of partially methylated or unmethylated.
In some embodiments, a recurrent tumor sample from a subject comprises a BRCA1 promoter methylation status that is fully methylated. In some embodiments, a subject may respond better to therapy with a platinum-based agent if a recurrent tumor sample from the subject has a promoter methylation status of fully methylated. In some embodiments, a subject may be selected for therapy with a platinum-based agent if a recurrent tumor sample from the subject has a promoter methylation status of fully methylated.
In some embodiments, a recurrent tumor sample from a subject comprises a BRCA1 promoter methylation status that is partially methylated or unmethylated. In some embodiments, a subject may respond better to an alternative therapy that does not include a platinum-based agent if a recurrent tumor sample from the subject has a promoter methylation status of partially methylated or unmethylated. In some embodiments, a subject may be selected for an alternative therapy that does not include a platinum-based agent if a recurrent tumor sample from the subject has a promoter methylation status of partially methylated or unmethylated.
The methods described herein, in some embodiments, comprise assaying a tumor sample for an immune signature. The term immune signature refers to a distinct molecular profile of a tumor (or tumor sample), taking into account the types of immune cells infiltrating the tumor (referred to as immune infiltrate), as well as the gene and/or protein expression profile of cells (resident or infiltrate) in the tumor (or tumor sample).
In some embodiments, an immune signature includes a gene expression signature, which may be determined, for example, by assessing DNA and/or RNA expression patterns and/or levels in a tumor (or tumor sample). Non-limiting examples of assays for assessing gene expression patterns and/or levels include RNA-SEQ, target capture RNAseq, microarray, quantitative PCR.
In some embodiments, an immune signature includes a protein expression and/or activity signature, which may be determined, for example, by assessing protein expression patterns, levels, and/or activity in a tumor (or tumor sample). Non-limiting examples of assays for assessing protein expression patterns, levels, and/or activity include immunohistochemical assays, immunocytochemical assays and Western Blotting.
In some embodiments, an immune signature includes an immune infiltrate signature, which may be determined, for example, by assessing, directly or indirectly, the types of immune cells present in a tumor (or tumor sample). Non-limiting examples of assays for assessing immune infiltrate include the gene and protein expression assays above as well as single cell RNAseq, CITE-seq and NanoString Technologies gene expression assays. Examples of cells that may be present in an immune infiltrate include lymphoid cells, such as cytotoxic T lymphocytes (CD3+·CD8+), regulatory T lymphocytes (CD3+, CD4+, CD25+, FOXP3+), T helper lymphocytes (CD4+) and natural killer cells (CD16+, CD56+), as well as myeloid cells, such as dendritic cells (CD40+), myeloid-derived suppressor cells (MDSC) (CD11b+, CD66b+) and macrophages (CD68+). In some embodiments, the following cell surface markers are used to assay an immune infiltrate of a tumor sample: PD-1, PD-L1, CD3, CD4, CD8, CD25, IFNγ, LAG3, and FoxP3. In some embodiments, an immune signature of the present invention refers to an immune infiltrate of a tumor sample. In some embodiments, an immune infiltrate may be a subset of an immune signature.
An immune signature may be assessed using one or more of a variety of different assays and algorithms known or later developed. For example, an immune signature may be generated using an algorithm capable of estimating abundances of member cell types in a mixed cell population using gene expression data (e.g., RNA-SEQ data). The output of such an algorithm is an abundance score for member cell types. The abundance score may be based on all immune cell types or a subset of immune cell subtypes, for example. In some embodiments, the algorithm used to estimate abundance of member cell types in a mixed cell population is trained on all immune cell subtypes (e.g., lymphoid cells and/or myeloid cells). In some embodiments, the algorithm used to estimate abundance of member cell types in a mixed cell population is trained on a subset of immune cell subtypes. Non-limiting examples of algorithms that could be used are associated with the following computational tools: the Microenvironment Cell Populations-Counter (MCP-counter) (Becht et al., 2016, incorporated by reference herein), the University of San Francisco xCell webtool, the Tumor Immune Estimation Resource (TIMER), and CIBERSORT (Chen et al. 2018, incorporated by reference herein).
In some embodiments, an immune signature of a tumor sample can be assayed by generating a tumor sample CIBERSORT score of a (at least one) immune cell-specific gene expression profile. In some embodiments, one immune cell-specific expression profile is used to generate a CIBERSORT score of a tumor sample. In some embodiments, two immune cell-specific expression profiles are used to generate two CIBERSORT scores of a tumor sample and the two CIBERSORT scores are considered together. In some embodiments, a CIBERSORT score is a M1 macrophage signal in a tumor sample.
An immune signature may also be assayed using a computational method that determines whether an a priori defined set of genes (e.g., gene sets) shows statistically significant, concordant differences between two biological states (e.g., tumor phenotype relative to normal phenotype). This computational method may be, for example, a Gene Set Enrichment Analysis (GSEA), wherein a gene set's enrichment score is generated with respect to phenotypic differences across a collection of a samples within a dataset. Many tools are available for performing a GSEA computational method, such as, Nucleic Acid SeQuence Analysis Resource (NASQAR), PlantRegMap, Molecular Signature Database (MSigDB), Broad Institute downloadable GSEA software, WebGestalt (a web based gene set analysis toolkit), Enrichr (a gene set enrichment analysis tool for mammalian gene sets), GeneSCF, the Database for Annotation, Visualization and Integrated Discovery (DAVID), Metascape, AmiGO 2 (a gene ontology enrichment tool), Genomic region enrichment of annotations tool (GREAT), the Functional Enrichment Analysis (FunRich), FuncAssociate (tool that enables gene ontology and custom enrichment analyses), InterMine, ToppGene Suite, Quantitative Set Analysis for Gene Expression (QuSAGE), Blast2GO, and g:Profiler. Other tools for performing a GSEA computation method known to those skilled in the art are also contemplated. In some embodiments, an immune signature of a tumor sample is assayed by an immune cell-specific enrichment score computed via a GSEA tool known or later developed.
The computational method may be, for example, a single-sample Gene Set Enrichment Analysis (ssGSEA), wherein a separate enrichment score for each pairing of sample and gene set, independent of phenotype labeling is generated. The ssGSEA computational method transforms a single sample's gene expression profile to a gene set enrichment profile. A gene set's enrichment score represents the activity level of the biological process in which the gene set's members are coordinately up-regulated or down-regulated. This transformation permits the cell state of a sample, such as a tumor sample, to be characterized in terms of the activity levels of biological processes and pathways rather than through the expression levels of individual genes. In some embodiments, an immune signature of a tumor sample is assayed by an immune cell-specific enrichment score computed via a ssGSEA tool known or later developed.
In some embodiments, an immune signature is assayed by using an immune cell-specific enrichment score computed via a ssGSEA immune-related gene set defined by Barbie et al. 2009, incorporated by reference herein. Such immune-related gene sets can be found, for example, at Molecular Signatures Database, (broad.mit.edu/gsea/msigdb/).
In some embodiments, an immune signature is assayed using immune gene set enrichment-based methods defined by Davoli et al. 2017, which is incorporated by reference herein. Such immune-related gene sets, which defined gene expression for immune cell types (e.g., CD8+ T cells, B cells, NK cells, Tregs, CD4+ T cells, dendritic cells, and macrophages) can be found, for example, at the Immunological Genome Project (ImmGen) database.
In some embodiments, the immune signature of the present disclosure is assayed by other immune-related gene set enrichment-based methods known or later developed.
In some embodiments, an immune signature can be determined using an immunomodulatory subtype assignment based on the TNBCtype classification system described by Chen at al. 2012, incorporated by reference herein. As used herein, the TNBCtype classification system refers to six triple negative breast cancer subtypes (e.g., basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL), and luminal androgen receptor (LAR)) identified by clustering analysis of 14 publicly available microarray data-sets. The immunomodulatory (IM) subtype includes canonical pathways such as the CTLA4 pathway, the IL12 pathway, the NK pathway, the Th1/Th2 pathway, the IL7 pathway, the antigen processing/presentation pathway, the NF-kB pathway, the TNF pathway, the T cell signal transduction pathway, the DC pathway, the BCR signaling pathway, the NK cell mediated cytotoxicity pathway, the JAK/STAT signaling pathway, and the ATR/BRCA pathway. In some embodiments, the immune signature of a tumor sample is assayed using the immunomodulatory subtype assignment based on the TNBCtype classification system described by Chen et al., 2012.
Other methods for assaying an immune signature of a tumor sample known to one of ordinary skill in the art are also contemplated.
The methods provided herein, in some embodiments, include comparing an immune signature to a threshold value. A threshold value is associated with a statistic. As used herein, it is a value above or below which an immune signature is assigned significance, in particular with respect to a subject's responsiveness to therapy with a platinum-based agent. See Examples section below. In some embodiments, a threshold value is a median value. In some embodiments, a threshold value is an average value. In some embodiments, a threshold value is a mean value.
In some embodiments provided herein, a subject is selected for a therapy with a platinum-based agent if a tumor sample has a wild-type BRCA1/2 gene mutational status and an immune signature above the threshold level. In other embodiments, a subject is selected for a therapy with a platinum-based agent if the tumor has a mutated BRCA1/2 gene mutational status. In yet other embodiments, a subject is selected for no therapy or a therapy other than a therapy with a platinum-based agent if the tumor sample has a wild-type BRCA1/2 gene mutational status and an immune signature below the threshold level.
The present disclosure provides a method for measuring the BRCA1/2 gene mutational status of a tumor sample from a subject. In some embodiments, the method further provides for categorizing the status of a subject with one of the following: a mutated BRCA1/2 gene mutational status or a wild-type BRCA1/2 gene mutational status.
In some embodiments, the method further identifies a subject as a candidate for platinum-based therapy based on the BRCA1/2 gene mutational status of their tumor sample. As used herein, “candidate” refers to a subject that may be responsive to a proposed treatment. As used herein, “platinum-based therapy” refers to administration of a platinum-based agent (i.e., a platinum-based therapeutic agent) to selectively kill or inhibit the growth, proliferation, and division of tumor cells.
The present disclosure provides, in some embodiments, the method for administering the platinum-based therapy to the subject based on the BRCA1/2 gene mutational status of the tumor sample from the subject. Administering can be by any method known in the art. Non-limiting examples of administering include intravenous, intraarterial, inhalation, ingestion of solid, ingestion of liquid, intradermal, intranasal, intramucosal, intraocular, intracranial, or intrathecal.
In some embodiments, a subject of the present disclosure is further categorized by how the subject is predicted to respond to the therapy. For example, a subject may be predicted to be a “good responder” or a “poor responder” to therapy based on the categorization of the BRCA1/2 gene mutational status of the tumor sample. As used herein, a good responder refers to a subject wherein the tumor may respond to treatment as indicated by a decrease in tumor size, an absence of secondary site tumors/metastases, and/or increased overall survival (OS) of the subject. As used herein, a poor responder refers to a subject wherein the tumor does not respond to treatment as indicated by the absence of a decrease in tumor size, the increase in tumor size, the presence of secondary site tumors/metastases, and/or an absence of increase in OS of the subject or a decrease in OS of the subject.
In some embodiments, a subject comprising a tumor with a mutated BRCA1/2 gene mutational status is predicted to be a good responder to the therapeutic agent. In some embodiments, the subject comprising a tumor with a mutated BRCA1/2 gene mutational status is selected for therapy with a platinum-based agent. In some embodiments, a platinum-based agent is administered to the subject with mutated BRCA1/2 gene mutational status.
In some embodiments, a subject comprising a wild-type BRCA1/2 gene mutational status tumor sample is further assayed for an immune signature above or below a determined threshold level. In some embodiments, wherein the immune signature is above the threshold level, the subject comprising a wild-type BRCA1/2 gene mutational status is selected for therapy with a platinum-based agent. In some embodiments, the subject is predicted to be a good responder to the therapeutic agent. In some embodiments, a platinum-based agent is administered to the subject with a wild-type BRCA1/2 gene mutational status wherein the immune signature is above the threshold level. In some embodiments, wherein the immune signature is below the threshold level, the subject is selected for no therapy or a therapy other than a therapy with a platinum-based agent. In some embodiments, the subject comprising a wild-type BRCA1/2 gene mutational status is predicted to be a poor responder to the therapeutic agent. In some embodiments, a platinum-based agent is not administered to the subject with a wild-type BRCA1/2 gene mutational status wherein the immune signature is below the threshold level.
Platinum-based agents contain a platinum molecule conjugated to organic molecules including amines (NH2), amides (NH3), and chlorides (Cl). Platinum-based agents are effective at killing tumor cells because they are conjugated to DNA and inhibit DNA transcription, replication and repair. Non-limiting examples of platinum-based agents includeoxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin. In certain embodiments, the platinum-based therapeutic agent is any one described in Apps et al., The state-of-play and future of platinum drugs. Endocrine-Related Cancer 22:R219-R233, 2015 (incorporated herein by reference).
In some embodiments, a platinum-based therapy for a subject with a mutated BRCA1/2 gene mutational status, a wild-type BRCA1/2 gene mutational status, or a BRCA1 gene methylation status is a single platinum-based agent.
In some embodiments, a platinum-based therapy for a subject with mutated BRCA1/2 gene mutational status, wild-type BRCA1/2 gene mutational status or BRCA1 gene methylation status is a platinum-based therapy, wherein a single platinum-based agent is selected from the group consisting of oxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin.
In some embodiments, a platinum-based therapy for a subject with a mutated BRCA1/2 gene mutational status, a wild-type BRCA1/2 gene mutational status or a BRCA1 gene methylation status is a single platinum-based agent and/or a combination of platinum-based agents, or at least one platinum-based agent in combination with at least one other agent (e.g., a combination therapy). For example, other agents may include alkylating agents (e.g., cyclophosphamide, mechlorethamine, chlorambucil, melphalan, dacarbazine, nitroureas, temozolomide), anthracyclines (e.g., daunorubicin, doxorubicin, epirubucin, idarubicin, mitoxantrone, valrubicin), taxanes (e.g., paclitaxel, docetaxel, cabazitaxel, abraxane, taxotere), histone deacetylase inhibitors (e.g., vorinostat and romidepsin), topoisomerase inhibitors (e.g., irinotecan, topotecan, etoposide, teniposide, tafluposide), kinase inhibitors (e.g., bortezomib, erlotinib, gefitinib, imatinib, vemurafenib, vismodegib), nucleotide analogs (e.g., azacitidine, azathioprine, capecitabine, cytarabine, doxifluridine, fluorouracil, gemcitabine, hydroxyurea, mercaptopurine, methotrexate, tioguanine), retinoids (e.g., tretinoin, alitretinoin, bexarotene), and vinca alkaloids and derivatives (e.g., vinblastine, vincristine, vindesine, vinorelbine).
In some embodiments, a platinum-based therapy for a subject with mutated BRCA1/2 gene mutational status, wild-type BRCA1/2 gene mutational status or BRCA1 gene methylation status is a combination platinum-based therapy wherein at least two platinum-based agents are selected from the group consisting of oxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin.
In some embodiments, a platinum-based therapy for a subject with mutated BRCA1/2 gene mutational status, wild-type BRCA1/2 gene mutational status or BRCA1 gene methylation status is a combination platinum-based therapy comprises one or more platinum-based agents selected from the group consisting of oxaliplatin, cisplatin, carboplatin, nedaplatin, picoplatin, phenanthriplatin, triplatin, spiroplatin, satraplatin, iproplatin, and satraplatin, and a taxane. In some embodiments, the combination therapy comprises cisplatin or carboplatin. In some embodiments, the taxane is selected from the group consisting of paclitaxel, docetaxel, and cabazitaxel.
Additional embodiments of the present disclosure are encompassed by the following numbered paragraphs:
To test the hypothesis that type 1 TDP status may be predictive of optimal response to platinum-based therapy, TDP status was assessed across a cohort of 42 TNBC patients undergoing neoadjuvant carboplatin and NAB-paclitaxel. All tumor specimens were collected as treatment-naïve biopsies before starting the neoadjuvant treatment. 45% of the tumors classified as TDP with (19/42,
Previously, it was determined that BRCA1 deficiency exhibited the identical effect on inducing the TDP in both TNBC and ovarian cancer (OvCa). If the primary genomic biology of TDP formation were the driver for this chemotherapeutic response, then it should hold across different disease types with the same genomic characteristics. Given that platinum-based chemotherapy is the preferred treatment for OvCa, and given that BRCA2 mutations are more common in OvCa than in TNBC, the hypothesis that BRCA1 or BRCA2 mutational status and not TDP status was predictive of patient response to platinum-based chemotherapy was studied.
In the first instance, publicly available data was reviewed for ovarian cancer cohorts with complete genome sequence information and response assessment. To this end, the only dataset with detailed response information along with whole genome sequencing and a high number of cases (N=80 primary tumors) was from the Australian Ovarian Cancer Study (AOCS,
Given the positive signal from the publicly available data, a more in-depth analysis was pursued in an independent ovarian cancer dataset. To this end, a new cohort of 68 primary ovarian carcinoma (OvCa) patients with detailed response data to therapy with a combination of carboplatin and a taxane-based chemotherapeutic agent was sequenced (in-house OvCa dataset,
In this OvCa cohort, the TDP type 1 configuration was again significantly associated with BRCA1-deficiency (30/34 (88.2%) vs. 4/32 (12.5%) for BRCA1 wild type tumors, P=4.4E-10,
When we examined the clinical response associations with BRCA1/2 status in this new OvCa cohort, again, we found that patients with tumors carrying a BRCA1/2 mutation, but not BRCA1 methylation, significantly associated with better clinical outcomes when compared to patients with BRCA1/2 wild type tumors, both in terms of response rates (70% vs. 41.4%, respectively, P=0.05,
Since this TNBC cohort was treated with a platinum salt in combination with a taxane, it is not possible to attribute the different rates of patient response associated with BRCA1/2 status specifically to the platinum-based treatment. The majority of clinical studies always use combination chemotherapy which makes it difficult to parse out the effects of individual agents. One of the objectives of our study is to ask whether TDP and/or BRCA1/2 status are the key determinants of platinum sensitivity in OvCa and TNBC. To this end, we analyzed a cohort of 33 TNBC patient-derived xenografts (PDXs), treated in vivo with single agent carboplatin (
Measures of homologous recombination deficiency (HRD) reflect TDP type 1 status and are not able to distinguish between BRCA1 mutant and methylated tumors, which confounds the prognostic utility of HRD scores for therapeutic response in ovarian and breast cancers.
Both BRCA1 mutation and promoter methylation resulted in the same TDP type 1 genomic configuration across all datasets analyzed in this study. However, these two modes of BRCA1 functional inactivation resulted in differential response to therapy. It was therefore hypothesized that mutations in the BRCA1 gene would result in stronger TDP phenotypes compared to BRCA1 promoter methylation. When TDP features across the union of the four examined cancer genome datasets were compared, it was found that while BRCA1 mutated and methylated genomes were both significantly different from BRCA1 wild type genomes, they were remarkably similar in terms of both mode of TD span size distribution, and TDP score, which combines measurements of TD number and genomic scattering (
It has been postulated that structural genomic instability as measured by HRD scores is a good measure of “BRCAness”, and high HRD scores have been associated with sensitivity to chemotherapy, especially to platinum-based therapies in ovarian cancers. In particular, the HRDetect score has been recently developed to combine and summarize a panel of genomic features associated with BRCA1 and/or BRCA2 deficiency, including the well-established HRD score (e.g., Timms et al. 2014, incorporated by reference herein), single substitution signatures 3 and 8, rearrangement signatures 3 and 5 and the presence of large deletions (>3bps) with microhomology at their junction (e.g., Davies et al. 2017, incorporated by reference herein). To further assess whether BRCA1 mutation and methylation would associate with differences in the type or degree of genomic scars that are linked to BRCAness, beyond the TDP, HRDetect scores between BRCA1 mutant and methylated TNBC and OvCA patients from a meta-cohort of 877 cancer genomes were compared. As expected, there was a highly significant association between both BRCA1 mutation and methylation status with high HRDetect scores (86.7% and 93.8% of each respectively, as compared to 13.9% of BRCA1/2 wild type genomes,
Even though the HRDetect score outperformed the TDP type 1 classifier in capturing BRCA2 deficiencies, these findings suggested that this indicator would suffer the same limitations as the TDP classifier when applied to predict chemo-responsiveness.
We then analyzed therapeutic response in a subset of the AOCS dataset with HRDetect scores and compared overall survival hazard ratios between subsets of patients either based on their BRCA1/2 status or classified using the HRDetect score. The HRDetect classifier was not able to identify the subset of best responders (
In BRCA1/2 wild type patients, optimal response to neoadjuvant carboplatin/nab-paclitaxel is associated with an enhanced immune signature and specifically a M1 macrophage immune genset expression profile in TNBC and ovarian carcinoma.
The next step of the study was to identify features that predict patient response in the absence of a BRCA1/2 mutation. RNAseq was used and the gene expression profiles of responders (i.e. pCR) was compared with non-responders (i.e. PR and SD) in the TNBC dataset. Each TNBC was first classified based on the TNBC-type transcriptional classification. Interestingly, when the 6-TNBC subtype classification method was applied, a significant enrichment was observed for the immunomodulatory subtype in the group of BRCA1/2 wild type tumors from patients who achieved pCR (7/15 (46.6%) vs. 1/18 (5.5%), OR=13.6, p=0.01, unclassified tumors are not included,
The next step was to see if the observed immune signature could be parsed out into different subsets of infiltrating immune cells. To this end, the CIBERSORT computational approach was applied to the RNA seq data and individual cell fractions from bulk tissue gene expression profiling were quantified. The CIBERSORT-generated scores relative to 22 distinct immune cell components between responder vs. non-responder tumor subgroups in the TNBC dataset were compared, as well as in the two ovarian carcinoma cohorts examined above. Remarkably, the M1 macrophage component was consistently increased in responders vs. non-responders across all three datasets examined. Again, this association was only found when analyzing the subset of BRCA1/2 wild type tumors (
The results strongly suggested that by considering BRCA1/2 mutational status and the expression of an immune signature in BRCA1/2 wild-type tumors, better predictions for chemo-responsiveness can be made than by using BRCA1/2 mutational status alone or HRD scores in TNBC and ovarian cancers. To test this, a response state was developed based on the presence of BRCA1/2 pathogenic mutations and, in the BRCA1/2 wild type tumor subset, on the strength of the M1 macrophage immune signature. Based on this decision tree, each tumor was given an assessment of good vs. poor vs. intermediate response, as indicated in the schematic in
This present disclosure confirmed that reduction of BRCA1 activity via either mutation or methylation robustly associates with type 1 TDPs in TNBC. However, TDP status did not predict good response, suggesting the separation of BRCA effects on genomic instability and platinum sensitivity. This indicated that genomic signature assessments, such as TDP and HRD, may not be sufficient in predicting pathologic complete response (pCR) in TNBC. Importantly, BRCA1/2 mutated TNBC patients were more likely to experience pCR (8/9) compared with patients with either BRCA1 methylation (4/11) or wild type BRCA1/2 (8/21). The exact genetic underpinnings of response in non-BRCA patients are currently under investigation.
Forty-two (42) patients with TNBC were enrolled in a phase II study of neoadjuvant carboplatin/nab-paclitaxel at the City of Hope National Medical Center (NCT01525966). Pathological complete response (pCR) was achieved in 50% of pts (21/42). Whole-genome sequencing (WGS) was performed using standard Illumina protocols. Structural variants were called using Crest, Delly and BreakDancer, and high confidence breakpoints were selected when called by at least two tools and by requiring split-read support. TDP status was ascertained as recently described (2). BRCA1 methylation was determined by methylation-specific PCR. Vanderbilt TNBC subtypes were determined using the TNBCtype-4 tool.
University of Washington (OvCa) dataset. A total of 68 serous ovarian carcinomas were selected from the Gynecologic Oncology Tissue Bank established by Prof. Elizabeth M. Swisher at the University of Washington, Seattle, WA, to represent extreme outcomes of patient survival but independently of any other genetic or clinical features. Australian Ovarian Cancer Study (AOCS). This dataset comprises 80 primary serous ovarian carcinomas that are part of the Australian ovarian cancer study (AOCS). Their BRCA1/2 status had been previously published (Patch et al., 2015). Structural variant calls were downloaded from the COSMIC data portal (data freeze version v78). Clinical data and RNAseq-based gene expression were downloaded from the ICGC data Portal (dcc.icgc.org/) in August 2020.
Tumor volumes in the control and treatment arm were assessed over a period of 28 days, with saline (control arm) and carboplatin (treatment arm) dosing on days 1, 7, 14 and 21. The rate of tumor growth for each animal in the study was computed by fitting a linear curve to the log-transformed tumor volumes. Finally, the percentage difference in tumor growth rate for each animal was calculated by comparing its tumor growth rate to the average growth rate of all the tumors in the control arm.
BRCA1 methylated tumors did not show the same sensitivity to platinum-based chemotherapies as BRCA1 mutated tumors, which was puzzling given the functional equivalence between the two states in terms of downstream genomic effects. To address this question, a total of 12 PDX models of BRCA1 methylated TNBC were first examined, combining the subset of BRCA1 methylated tumors from the PDX cohort described above and additional BRCA1 methylated tumors available from The Jackson Laboratory PDX Resource, all of which shared the TDP Type 1 configuration and whose patient donors' clinical histories prior to the model establishment were available. Two modes of BRCA1 promoter methylation were observed, as assessed by Methylation-Specific PCR (MSP): (a) full methylation (i.e., no signal for the unmethylated PCR product) and (b) partial methylation (i.e., two signals corresponding to both the methylated and the unmethylated PCR products,
The relationship between BRCA1 methylation status and treatment exposure was further investigated using three PDX models, WHIM68, WHIM69 and WHIM74, established from subsequent biopsies and surgical specimens from the same TNBC patient donor: WHIM68 was established from a pre-neoadjuvant treatment biopsy and it was therefore treatment-naïve, WHIM69 was derived from a research biopsy taken at day 3 after the first cycle of neoadjuvant treatment with carboplatin and docetaxel; and WHIM74 was derived from a surgical specimen obtained after the completion of the neoadjuvant course (
It was then evaluated whether direct treatment with chemotherapy of a PDX can cause loss of BRCA1 methylation, by selecting a single fully methylated TNBC PDX established from a treatment-naïve patient tumor (TM00097) and subjecting it to treatment with four weekly doses of either cisplatin or vehicle control, followed by continuous monitoring of tumor recurrence (
To test whether similar trends would translate to the clinical setting, the BRCA1 methylation status of the UW OvCa cohort was re-assessed via quantitative MS-ddPCR. After correcting for the proportion of neoplastic cellularity, the degree of BRCA1 methylation showed a significant negative correlation with BRCA1 expression levels (r=−0.82, P=0.0006,
A proposed hypothesis for the loss of BRCA1 methylation following chemotherapeutic treatment and the emergence of resistant tumor recurrences, is the rapid expansion of a non-methylated subclone from a heterogeneous tumor cell population that contained BRCA1 methylated and BRCA1 proficient clones. In a previous AOCS study, a patient initially diagnosed with a BRCA1 methylated, platinum sensitive primary ovarian carcinoma recurred with a tumor that was completely unmethylated and chemo resistant. Based on the unexpected observation of a minimal overlap between the somatic single nucleotide mutations observed in primary and the recurrent tumors, it was speculated that the recurrence may have originated from an original BRCA1 non-methylated (therefore BRCA1 proficient) and platinum resistant subclone, which was expanded during the chemotherapeutic treatment. In previous work, it was found that BRCA1 deficiency is a prerequisite for the generation of a TDP genomic configuration in the resultant tumors and potentially is the earliest inciting event. Through a detailed genomic analysis of structural mutations in this tumor pair, it was found that, despite featuring a predominance of private rearrangements, both the primary and the recurrent cancer genomes classified as TDP type 1 (
Taken together, these data suggest that BRCA1 deficiency due to promoter methylation can be overridden by demethylation of one allele associated with induction of wild type BRCA1 expression, and that this reversion of the methylated state can occur after only a short course of platinum chemotherapy. Finally, once this partially methylated state is established, the resultant tumor exhibits relative resistance to platinum drugs akin to BRCA1 wild type tumors.
All references, patents and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.
The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”
It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.
In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.
The terms “about” and “substantially” preceding a numerical value mean±10% of the recited numerical value.
Where a range of values is provided, each value between the upper and lower ends of the range are specifically contemplated and described herein.
This application is a national stage filing under 35 U.S.C. § 371 of International Patent Application Serial No. PCT/US2022/011767, filed Jan. 10, 2022, entitled “Prognostic Methods for Platinum-Based Chemotherapeutics,” which claims the benefit under 35 U.S.C. § 1 19(e) of U.S. Provisional Application No. 63/137,853, filed Jan. 15, 2021, entitled “Prognostic Methods for Platinum-Based Chemotherapeutics,” and U.S. Provisional Application No. 63/232,907, filed Aug. 13, 2021, entitled “Prognostic Methods for Platinum-Based Chemotherapeutics,” the contents of each of which are hereby incorporated by reference in their entirety.
This invention was made with government support under P30CA034196 awarded by National Institutes of Health and W81XWH-17-1-0005 awarded by Department of Defense. The government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2022/011767 | 1/10/2022 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63232907 | Aug 2021 | US | |
| 63137853 | Jan 2021 | US |
