Person:

Richards, William

With the emergence of checkpoint blockade and other immunotherapeutic drugs, and the growing adoption of smaller, more flexible adaptive clinical trial designs, there is an unmet need to develop diagnostics that can rapidly immunophenotype patient tumors. The ability to longitudinally profile the tumor immune infiltrate in response to immunotherapy also presents a window of opportunity to illuminate mechanisms of resistance. We have developed a fine needle aspirate biopsy (FNA) platform to perform immune profiling on thoracic malignancies. Matching peripheral blood, bulk resected tumor, and FNA were analyzed from 13 mesothelioma patients. FNA samples yielded greater numbers of viable cells when compared to core needle biopsies. Cell numbers were adequate to perform flow cytometric analyses on T cell lineage, T cell activation and inhibitory receptor expression, and myeloid immunosuppressive checkpoint markers. FNA samples were representative of the tumor as a whole as assessed by head-to-head comparison to single cell suspensions of dissociated whole tumor. Parallel analysis of matched patient blood enabled us to establish quality assurance criteria to determine the accuracy of FNA procedures to sample tumor tissue. FNA biopsies provide a diagnostic to rapidly phenotype the tumor immune microenvironment that may be of great relevance to clinical trials.

Abstract Background: Analysis of the International Association for the Study of Lung Cancer (IASLC) Malignant Pleural Mesothelioma (MPM) database revealed that clinical (cTNM) staging minimally stratified survival and was discrepant with pathological (pTNM) staging. To improve prognostic classification of MPM, alternative staging models based on quantitative parameters were explored. Methods: An institutional review board–approved MPM registry was queried to identify patients with available pathological and preoperative imaging data. Qualifying patients were randomly assigned to training and test sets in a 1:2 ratio. Computed cTNM and pTNM staging (AJCC Cancer Staging Manual, 7th ed.) were compared. Quantitative image analysis included tumor volume assessed from three-dimensional reconstruction of computed tomography scans (VolCT) and maximal fissural thickness (Fmax). Survival was estimated using the Kaplan-Meier method, and the relationship with VolCT was examined by Cox regression analysis to identify optimized cut-points. Performance of cTNM and quantitative models derived was compared in the test set using Harrell’s C index. Results: A total of 472 patients met inclusion criteria. TNM staging was concordant with pathological TNM staging in 171 of 472 (36.2%), understaged in 209 (44.2%), and overstaged in 92 (19.4%) patients. The most concordant feature was involvement of interlobar fissures. A quantitative clinical staging model comprising VolCT and Fmax (c-index = 0.638, 95% confidence interval [CI] = 0.603 to 0.673) performed statistically significantly better as a prognostic classifier when compared in the test set with cTNM (c-index = 0.562, 95% CI = 0.525 to 0.599, P = .001). Conclusions: Improved prognostic performance may be achievable by quantitative clinical staging combining VolCT and Fmax, providing a cost-effective and clinically relevant surrogate for clinical TNM stage.

Cancers arise by the gradual accumulation of mutations in multiple genes. We now use shotgun pyrosequencing to characterize RNA mutations and expression levels unique to malignant pleural mesotheliomas (MPMs) and not present in control tissues. On average, 266 Mb of cDNA were sequenced from each of four MPMs, from a control pulmonary adenocarcinoma (ADCA), and from normal lung tissue. Previously observed differences in MPM RNA expression levels were confirmed. Point mutations were identified by using criteria that require the presence of the mutation in at least four reads and in both cDNA strands and the absence of the mutation from sequence databases, normal adjacent tissues, and other controls. In the four MPMs, 15 nonsynonymous mutations were discovered: 7 were point mutations, 3 were deletions, 4 were exclusively expressed as a consequence of imputed epigenetic silencing, and 1 was putatively expressed as a consequence of RNA editing. Notably, each MPM had a different mutation profile, and no mutated gene was previously implicated in MPM. Of the seven point mutations, three were observed in at least one tumor from 49 other MPM patients. The mutations were in genes that could be causally related to cancer and included XRCC6, PDZK1IP1, ACTR1A, and AVEN.

The current paradigm for elucidating the molecular etiology of cancers relies on the interrogation of small numbers of genes, which limits the scope of investigation. Emerging second-generation massively parallel DNA sequencing technologies have enabled more precise definition of the cancer genome on a global scale. We examined the genome of a human primary malignant pleural mesothelioma (MPM) tumor and matched normal tissue by using a combination of sequencing-by-synthesis and pyrosequencing methodologies to a 9.6X depth of coverage. Read density analysis uncovered significant aneuploidy and numerous rearrangements. Method-dependent informatics rules, which combined the results of different sequencing platforms, were developed to identify and validate candidate mutations of multiple types. Many more tumor-specific rearrangements than point mutations were uncovered at this depth of sequencing, resulting in novel, large-scale, inter- and intra-chromosomal deletions, inversions, and translocations. Nearly all candidate point mutations appeared to be previously unknown SNPs. Thirty tumor-specific fusions/translocations were independently validated with PCR and Sanger sequencing. Of these, 15 represented disrupted gene-encoding regions, including kinases, transcription factors, and growth factors. One large deletion in DPP10 resulted in altered transcription and expression of DPP10 transcripts in a set of 53 additional MPM tumors correlated with survival. Additionally, three point mutations were observed in the coding regions of NKX6-2, a transcription regulator, and NFRKB, a DNA-binding protein involved in modulating NFKB1. Several regions containing genes such as PCBD2 and DHFR, which are involved in growth factor signaling and nucleotide synthesis, respectively, were selectively amplified in the tumor. Second-generation sequencing uncovered all types of mutations in this MPM tumor, with DNA rearrangements representing the dominant type.

Malignant pleural mesothelioma (MPM) is an aggressive cancer that occurs more frequently in men, but is associated with longer survival in women. Insight into the survival advantage of female patients may advance the molecular understanding of MPM and identify therapeutic interventions that will improve the prognosis for all MPM patients. In this study, we performed whole-genome sequencing of tumor specimens from 10 MPM patients and matched control samples to identify potential driver mutations underlying MPM. We identified molecular differences associated with gender and histology. Specifically, single-nucleotide variants of BAP1 were observed in 21% of cases, with lower mutation rates observed in sarcomatoid MPM (p<0.001). Chromosome 22q loss was more frequently associated with the epithelioid than that non-epitheliod histology (p=0.037), whereas CDKN2A deletions occurred more frequently in non-epithelioid subtypes among men (p=0.021) and were correlated with shorter overall survival for the entire cohort (p=0.002) and for men (p=0.012). Furthermore, women were more likely to harbor TP53 mutations (p=0.004). Novel mutations were found in genes associated with the integrin-linked kinase pathway, including MYH9 and RHOA. Moreover, expression levels of BAP1, MYH9, and RHOA were significantly higher in non-epithelioid tumors, and were associated with significant reduction in survival of the entire cohort and across gender subgroups. Collectively, our findings indicate that diverse mechanisms highly related to gender and histology appear to drive MPM.

Purpose To develop a standardized approach for molecular diagnostics, we used the gene-expression ratio bioinformatic technique to design a molecular signature to diagnose MPM from among other potentially confounding diagnoses and differentiate the epithelioid from the sarcomatoid histological subtype of MPM. In addition, we searched for pathways relevant in MPM in comparison to other related cancers to identify unique molecular features in MPM.

Experimental Design We performed microarray analysis on 113 specimens including MPMs and a spectrum of tumors and benign tissues comprising the differential diagnosis of MPM. We generated a sequential combination of binary gene-expression ratio tests able to discriminate MPM from other thoracic malignancies. We compared this method to other bioinformatic tools and validated this signature in an independent set of 170 samples. Functional enrichment analysis was performed to identify differentially expressed probes.

Results A sequential combination of gene-expression ratio tests was the best molecular approach to distinguish MPM from all the other samples. Bioinformatic and molecular validations showed that the sequential gene ratio tests were able to identify the MPM samples with high sensitivity and specificity. In addition, the gene-ratio technique was able to differentiate the epithelioid from the sarcomatoid type of MPM. Novel genes and pathways specifically activated in MPM were identified.

Conclusions New clinically relevant molecular tests have been generated using a small number of genes to accurately distinguish MPMs from other thoracic samples supporting our hypothesis that the gene-expression ratio approach could be a useful tool in the differential diagnosis of cancers.