ABSTRACT
Purpose: Intratumoral genetic heterogeneity (ITGH) is a common feature of solid tumors. However, little is known about the effect of neoadjuvant chemoradiation (nCRT) in ITGH of rectal tumors that exhibit poor response to nCRT. Here, we examined the impact of nCRT in the mutational profile and ITGH of rectal tumors and its adjacent irradiated normal mucosa in the setting of incomplete response to nCRT. Methods and Materials: To evaluate ITGH in rectal tumors, we analyzed whole-exome sequencing (WES) data from 79 tumors obtained from The Cancer Genome Atlas (TCGA). We also compared matched peripheral blood cells, irradiated normal rectal mucosa and pre and post-treatment tumor samples (PRE-T and POS-T) from one individual to examine the iatrogenic effects of nCRT. Finally, we performed WES of 7 PRE-T/POST-T matched samples to examine how nCRT affects ITGH. ITGH was assessed by quantifying subclonal mutations within individual tumors using the Mutant-Allele Tumor Heterogeneity score (MATH score). Results: Rectal tumors exhibit remarkable ITGH that is ultimately associated with disease stage (MATH score stage I/II 35.54 vs. stage III/IV 44.39, p = 0.047) and lymph node metastasis (MATH score N0 35.87 vs. N+ 45.79, p = 0.026). We also showed that nCRT does not seem to introduce detectable somatic mutations in the irradiated mucosa. Comparison of PRE-T and POST-T matched samples revealed a significant increase in ITGH in 5 out 7 patients and MATH scores were significantly higher after nCRT (median 41.7 vs. 28.8, p = 0.04). Finally, we were able to identify a subset of "enriched mutations" with significant changes in MAFs between PRE-T and POST-T samples. These "enriched mutations" were significantly more frequent in POST-T compared to PRE-T samples (92.9% vs. 7.1% p < 0.00001) and include mutations in genes associated with genetic instability and drug resistance in colorectal cancer, indicating the expansion of tumor cell subpopulations more prone to resist to nCRT. Conclusions: nCRT increases ITGH and may result in the expansion of resistant tumor cell populations in residual tumors. The risk of introducing relevant somatic mutations in the adjacent mucosa is minimal but non-responsive tumors may have potentially worse biological behavior when compared to their untreated counterparts. This was an exploratory study, and due to the limited number of samples analyzed, our results need to be validated in larger cohorts.
ABSTRACT
Preclinical in vitro models provide an essential tool to study cancer cell biology as well as aid in translational research, including drug target identification and drug discovery efforts. For any model to be clinically relevant, it needs to recapitulate the biology and cell heterogeneity of the primary tumor. We recently developed and described a conditional reprogramming (CR) cell technology that addresses many of these needs and avoids the deficiencies of most current cancer cell lines, which are usually clonal in origin. Here, we used the CR cell method to generate a collection of patient-derived cell cultures from non-small cell lung cancers (NSCLC). Whole exome sequencing and copy number variations are used for the first time to address the capability of CR cells to keep their tumor-derived heterogeneity. Our results indicated that these primary cultures largely maintained the molecular characteristics of the original tumors. Using a mutant-allele tumor heterogeneity (MATH) score, we showed that CR cells are able to keep and maintain most of the intra-tumoral heterogeneity, suggesting oligoclonality of these cultures. CR cultures therefore represent a pre-clinical lung cancer model for future basic and translational studies.
Subject(s)
Carcinoma, Non-Small-Cell Lung/pathology , Cellular Reprogramming Techniques/methods , Genetic Heterogeneity , Gene Dosage , Humans , Models, Biological , Tumor Cells, Cultured , Whole Genome SequencingABSTRACT
Tumors develop numerous strategies to fine-tune inflammation and avoid detection and eradication by the immune system. The identification of mechanisms leading to local immune dysregulation is critical to improve cancer therapy. We here demonstrate that Interleukin-1 receptor 8 (IL-1R8 - previously known as SIGIRR/TIR8), a negative regulator of Toll-Like and Interleukin-1 Receptor family signaling, is up-regulated during breast epithelial cell transformation and in primary breast tumors. IL-1R8 expression in transformed breast epithelial cells reduced IL-1-dependent NF-κB activation and production of pro-inflammatory cytokines, inhibited NK cell activation and favored M2-like macrophage polarization. In a murine breast cancer model (MMTV-neu), IL-1R8-deficiency reduced tumor growth and metastasis and was associated with increased mobilization and activation of immune cells, such as NK cells and CD8+ T cells. Finally, immune-gene signature analysis in clinical specimens revealed that high IL-1R8 expression is associated with impaired innate immune sensing and T-cell exclusion from the tumor microenvironment. Our results indicate that high IL-1R8 expression acts as a novel immunomodulatory mechanism leading to dysregulated immunity with important implications for breast cancer immunotherapy.
Subject(s)
Breast Neoplasms/genetics , Breast Neoplasms/immunology , Gene Expression Regulation, Neoplastic , Immunity/genetics , Receptors, Interleukin-1/genetics , Animals , Breast Neoplasms/pathology , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , Cell Line, Tumor , Cell Transformation, Neoplastic/genetics , Cell Transformation, Neoplastic/immunology , Cytokines/metabolism , Dendritic Cells/immunology , Dendritic Cells/metabolism , Disease Models, Animal , Female , Gene Expression Profiling , Humans , Immunity, Innate/genetics , Immunomodulation , Inflammation Mediators/metabolism , Killer Cells, Natural/immunology , Killer Cells, Natural/metabolism , Mice , Mice, Knockout , NF-kappa B/metabolism , Tumor Escape/geneticsABSTRACT
OBJECTIVE: Demonstrate intratumoral genetic heterogeneity in rectal cancer. BACKGROUND: Several clinical management decisions in rectal cancer may be influenced by pretreatment biopsy information. However, in the setting of significant intratumoral heterogeneity, biopsies may not be representative of the entirety of the tumor and limit the reliability of the information provided from them for clinical decision management. METHODS: Three fragments from a single rectal adenocarcinoma were chosen for whole-exome sequencing followed by mutation detection analysis. About 25 Gb of unambiguously mapped sequences were generated for each sample resulting in a median fold-coverage of 35x. Captured sequences mapped to the reference human genome were then used for the detection of somatic point mutations. RESULTS: Overall, 193 unique somatic point mutations were identified. Only 53 (27%) of these were shared by all three fragments, including known genes involved in early phases of the adenoma-carcinoma sequence (such as, APC). Approximately, 115 (59%) mutations were exclusively present in only one of the fragments, including mutations in "driver" genes (DNAH12). Jaccard distances showed a median distance of 0.603 for pair-wise comparison of fragments indicating significant heterogeneity between them. CONCLUSIONS: Considerable intratumoral heterogeneity is present among naive rectal cancers. The majority of point mutations detected in different fragments from rectal cancers are frequently unique to a single fragment. These findings support that gene mutations found on single pretreatment biopsies will not necessarily be representative of mutations present in the entirety of the tumor and therefore may limit the utility of the biological information provided by single biopsy fragments for clinical management decisions.
Subject(s)
Adenocarcinoma/genetics , DNA, Neoplasm/analysis , Genetic Heterogeneity , Mutation , Rectal Neoplasms/genetics , Rectum/pathology , Adenocarcinoma/pathology , Biopsy , DNA Mutational Analysis , Exome , Humans , Rectal Neoplasms/pathologyABSTRACT
BACKGROUND: Glioblastoma (GBM) is the most common and aggressive type of brain tumor. Currently, GBM has an extremely poor outcome and there is no effective treatment. In this context, genomic and transcriptomic analyses have become important tools to identify new avenues for therapies. RNA-binding proteins (RBPs) are master regulators of co- and post-transcriptional events; however, their role in GBM remains poorly understood. To further our knowledge of novel regulatory pathways that could contribute to gliomagenesis, we have conducted a systematic study of RBPs in GBM. RESULTS: By measuring expression levels of 1542 human RBPs in GBM samples and glioma stem cell samples, we identified 58 consistently upregulated RBPs. Survival analysis revealed that increased expression of 21 RBPs was also associated with a poor prognosis. To assess the functional impact of those RBPs, we modulated their expression in GBM cell lines and performed viability, proliferation, and apoptosis assays. Combined results revealed a prominent oncogenic candidate, SNRPB, which encodes core spliceosome machinery components. To reveal the impact of SNRPB on splicing and gene expression, we performed its knockdown in a GBM cell line followed by RNA sequencing. We found that the affected genes were involved in RNA processing, DNA repair, and chromatin remodeling. Additionally, genes and pathways already associated with gliomagenesis, as well as a set of general cancer genes, also presented with splicing and expression alterations. CONCLUSIONS: Our study provides new insights into how RBPs, and specifically SNRPB, regulate gene expression and directly impact GBM development.
Subject(s)
Brain Neoplasms/genetics , Cell Transformation, Neoplastic/genetics , Gene Expression Regulation, Neoplastic , Genomics , Glioblastoma/genetics , RNA Splicing/genetics , RNA-Binding Proteins/genetics , snRNP Core Proteins/genetics , Apoptosis/genetics , Brain Neoplasms/metabolism , Brain Neoplasms/mortality , Brain Neoplasms/pathology , Cell Proliferation , Cell Survival/genetics , Cluster Analysis , Computational Biology/methods , Exons , Gene Expression Profiling , Gene Knockdown Techniques , Genomics/methods , Glioblastoma/metabolism , Glioblastoma/mortality , Glioblastoma/pathology , Humans , Introns , Molecular Sequence Annotation , Neoplasm Grading , Prognosis , RNA-Binding Proteins/metabolism , Signal Transduction , Transcriptome , snRNP Core Proteins/metabolismABSTRACT
Cancer gene panels (CGPs) are already used in clinical practice to match tumor's genetic profile with available targeted therapies. We aimed to determine if CGPs could also be applied to estimate tumor mutational load and predict clinical benefit to PD-1 and CTLA-4 checkpoint blockade therapy. Whole-exome sequencing (WES) mutation data obtained from melanoma and non-small cell lung cancer (NSCLC) patients published by Snyder et al. 2014 and Rizvi et al. 2015, respectively, were used to select nonsynonymous somatic mutations occurring in genes included in the Foundation Medicine Panel (FM-CGP) and in our own Institutional Panel (HSL-CGP). CGP-mutational load was calculated for each patient using both panels and was associated with clinical outcomes as defined and reported in the original articles. Higher CGP-mutational load was observed in NSCLC patients presenting durable clinical benefit (DCB) to PD-1 blockade (FM-CGP P=0.03, HSL-CGP P=0.01). We also observed that 69% of patients with high CGP-mutational load experienced DCB to PD-1 blockade, as compared to 20% of patients with low CGP-mutational load (FM-CGP and HSL-CGP P=0.01). Noteworthy, predictive accuracy of CGP-mutational load for DCB was not statistically different from that estimated by WES sequencing (P=0.73). Moreover, a high CGP-mutational load was significantly associated with progression-free survival (PFS) in patients treated with PD-1 blockade (FM-CGP P=0.005, HR 0.27, 95% IC 0.105 to 0.669; HSL-CGP P=0.008, HR 0.29, 95% IC 0.116 to 0.719). Similar associations between CGP-mutational load and clinical benefit to CTLA-4 blockade were not observed. In summary, our data reveals that CGPs can be used to estimate mutational load and to predict clinical benefit to PD-1 blockade, with similar accuracy to that reported using WES.