Dissection of a Down syndrome-associated trisomy to separate the gene dosage-dependent and -independent effects of an extra chromosome.

As an aneuploidy, trisomy is associated with mammalian embryonic and postnatal abnormalities. Understanding the underlying mechanisms involved in mutant phenotypes is broadly important and may lead to new strategies to treat clinical manifestations in individuals with trisomies, such as trisomy 21 [Down syndrome (DS)]. Although increased gene dosage effects because of a trisomy may account for the mutant phenotypes, there is also the possibility that phenotypic consequences of a trisomy can arise because of the presence of a freely segregating extra chromosome with its own centromere, i.e. a 'free trisomy' independent of gene dosage effects. Presently, there are no reports of attempts to functionally separate these two types of effects in mammals. To fill this gap, here we describe a strategy that employed two new mouse models of DS, Ts65Dn;Df(17)2Yey/+ and Dp(16)1Yey/Df(16)8Yey. Both models carry triplications of the same 103 human chromosome 21 gene orthologs; however, only Ts65Dn;Df(17)2Yey/+ mice carry a free trisomy. Comparison of these models revealed the gene dosage-independent impacts of an extra chromosome at the phenotypic and molecular levels for the first time. They are reflected by impairments of Ts65Dn;Df(17)2Yey/+ males in T-maze tests when compared with Dp(16)1Yey/Df(16)8Yey males. Results from the transcriptomic analysis suggest the extra chromosome plays a major role in trisomy-associated expression alterations of disomic genes beyond gene dosage effects. This model system can now be used to deepen our mechanistic understanding of this common human aneuploidy and obtain new insights into the effects of free trisomies in other human diseases such as cancers.

Cancer testis antigen burden (CTAB): a novel biomarker of tumor-associated antigens in lung cancer.

BACKGROUND: Cancer-testis antigens (CTAs) are tumor antigens that are normally expressed in the testes but are aberrantly expressed in several cancers. CTA overexpression drives the metastasis and progression of lung cancer, and is associated with poor prognosis. To improve lung cancer diagnosis, prognostic prediction, and drug discovery, robust CTA identification and quantitation is needed. In this study, we examined and quantified the co-expression of CTAs in lung cancer to derive cancer testis antigen burden (CTAB), a novel biomarker of immunotherapy response. METHODS: Formalin fixed paraffin embedded (FFPE) tumor samples in discovery cohort (n = 5250) and immunotherapy and combination therapy treated non-small cell lung cancer (NSCLC) retrospective (n = 250) cohorts were tested by comprehensive genomic and immune profiling (CGIP), including tumor mutational burden (TMB) and the mRNA expression of 17 CTAs. PD-L1 expression was evaluated by IHC. CTA expression was summed to derive the CTAB score. The median CTAB score for the discovery cohort of 170 was applied to the retrospective cohort as cutoff for CTAB "high" and "low". Biomarker and gene expression correlation was measured by Spearman correlation. Kaplan-Meier survival analyses were used to detect overall survival (OS) differences, and objective response rate (ORR) based on RECIST criteria was compared using Fisher's exact test. RESULTS: The CTAs were highly co-expressed (p < 0.05) in the discovery cohort. There was no correlation between CTAB and PD-L1 expression (R = 0.011, p = 0.45) but some correlation with TMB (R = 0.11, p = 9.2 × 10-14). Kaplan-Meier survival analysis of the immunotherapy-treated NSCLC cohort revealed better OS for the pembrolizumab monotherapy treated patients with high CTAB (p = 0.027). The combination group demonstrated improved OS compared to pembrolizumab monotherapy group (p = 0.04). The pembrolizumab monotherapy patients with high CTAB had a greater ORR than the combination therapy group (p = 0.02). CONCLUSIONS: CTA co-expression can be reliably measured using CGIP in solid tumors. As a biomarker, CTAB appears to be independent from PD-L1 expression, suggesting that CTAB represents aspects of tumor immunogenicity not measured by current standard of care testing. Improved OS and ORR for high CTAB NSCLC patients treated with pembrolizumab monotherapy suggests a unique underlying aspect of immune response to these tumor antigens that needs further investigation.

Clinical and Biologic Correlates of ADORA2A Transcriptomic Expression in Cancer.

ADORA2A (adenosine A2a receptor) and ADORA2B propagate immunoregulatory signals, including restricting both innate and adaptive immunity, though recent data also suggest a tumor suppressor effect in certain settings. We evaluated the RNA expression from 514 tumors in a clinical-grade laboratory; 489 patients with advanced/metastatic disease had clinical outcome correlates. Transcript expression was standardized to internal housekeeping genes and ranked (0-100 scale) relative to 735 specimens from 35 different cancer types. Transcript abundance rank values were defined as "low/moderate" (0-74) or "high" (75-100) percentile RNA expression ranks. Overall, 20.8% of tumors had high ADORA2A (≥75 percentile RNA rank). The greatest proportion of high ADORA2A expressors was found in neuroendocrine and breast cancers and sarcomas, whereas the lowest was found in colorectal and ovarian cancers, albeit with patient-to-patient variability. In multivariable logistic regression analysis, there was a significant positive correlation between high ADORA2A RNA expression and a high expression of the immune checkpoint-related molecules PD-1 (p = 0.015), VISTA (p ≤ 0.001), CD38 (p = 0.031), and CD39 (p ≤ 0.001). In 217 immunotherapy-treated patients, high ADORA2A did not correlate significantly with progression-free (p = 0.51) or overall survival (OS) (p = 0.09) from the initiation of the checkpoint blockade. However, high versus not-high ADORA2A transcript expression correlated with longer OS from the time of advanced/metastatic disease (N = 489 patients; (HR 0.69 (95% CI 0.51-0.95) (p = 0.02)). Therefore, high ADORA2A transcript levels may be a favorable prognostic factor, unrelated to immunotherapy. Importantly, ascertaining co-expression patterns of ADORA2A with PD-1 and VISTA in individual tumors as a basis for the precision co-targeting of ADORA2A and these other checkpoint-related molecules warrants investigation in clinical trials.

Identification of targets for prostate cancer immunotherapy.

BACKGROUND: We performed profiling of the immune microenvironment of castration-resistant (CRPC) and castration-sensitive (CSPC) prostate cancer (PC) in order to identify novel targets for immunotherapy. METHODS: PD-L1 and CD3/CD8 immunohistochemistry, PD-L1/2 fluorescent in situ hybridization, tumor mutation burden, microsatellite instability, and RNA-seq of 395 immune-related genes were performed in 19 CRPC and CSPC. Targeted genomic sequencing and fusion analysis were performed in 17 of these specimens. RESULTS: CD276, PVR, and NECTIN2 were highly expressed in PC. Comparison of CRPC versus CSPC and primary versus metastatic tissue revealed the differential expression of immunostimulatory, immunosuppressive, and epithelial-to-mesenchymal transition (EMT)-related genes. Unsupervised clustering of differentially expressed genes yielded two final clusters best segregated by CRPC and CSPC status. CONCLUSION: CD276 and the alternative checkpoint inhibition PVR/NECTIN2/CD226/TIGIT pathway emerged as relevant to PC checkpoint inhibition target development.

Comparison of SureSelect and Nextera Exome Capture Performance in Single-Cell Sequencing.

BACKGROUND: Advances in single-cell sequencing provide unprecedented opportunities for clinical examination of circulating tumor cells, cancer stem cells, and other rare cells responsible for disease progression and drug resistance. On the genomic level, single-cell whole exome sequencing (scWES) started to gain popularity with its unique potentials in characterizing mutational landscapes at a single-cell level. Currently, there is little known about the performance of different exome capture kits in scWES. Nextera rapid capture (NXT; Illumina, Inc.) has been the only exome capture kit recommended for scWES by Fluidigm C1, a widely accessed system in single-cell preparation. RESULTS: In this study, we compared the performance of NXT following Fluidigm's protocol with Agilent SureSelectXT Target Enrichment System (AGL), another exome capture kit widely used for bulk sequencing. We created DNA libraries of 192 single cells isolated from spheres grown from a melanoma specimen using Fluidigm C1. Twelve high-yield cells were selected to perform dual-exome capture and sequencing using AGL and NXT in parallel. After mapping and coverage analysis, AGL outperformed NXT in coverage uniformity, mapping rates of reads, exome capture rates, and low PCR duplicate rates. For germline variant calling, AGL achieved better performance in overlap with known variants in dbSNP and transition-transversion ratios. Using calls from high coverage bulk sequencing from blood DNA as the golden standard, AGL-based scWES demonstrated high positive predictive values, and medium to high sensitivity. Lastly, we evaluated somatic mutation calling by comparing single-cell data with the matched blood sequence as control. On average, 300 mutations were identified in each cell. In 10 of 12 cells, higher numbers of mutations were identified using AGL than NXT, probably caused by coverage depth. When mutations are adequately covered in both AGL and NXT data, the two methods showed very high concordance (93-100% per cell). CONCLUSIONS: Our results suggest that AGL can also be used for scWES when there is sufficient DNA, and it yields better data quality than the current Fluidigm's protocol using NXT.

Treatment recommendations to cancer patients in the context of FDA guidance for next generation sequencing.

BACKGROUND: Regulatory approval of next generation sequencing (NGS) by the FDA is advancing the use of genomic-based precision medicine for the therapeutic management of cancer as standard care. Recent FDA guidance for the classification of genomic variants based on clinical evidence to aid clinicians in understanding the actionability of identified variants provided by comprehensive NGS panels has also been set forth. In this retrospective analysis, we interpreted and applied the FDA variant classification guidance to comprehensive NGS testing performed for advanced cancer patients and assessed oncologist agreement with NGS test treatment recommendations. METHODS: NGS comprehensive genomic profiling was performed in a CLIA certified lab (657 completed tests for 646 patients treated at Roswell Park Comprehensive Cancer Center) between June 2016 and June 2017. Physician treatment recommendations made within 120 days post-test were gathered from tested patients' medical records and classified as targeted therapy, precision medicine clinical trial, immunotherapy, hormonal therapy, chemotherapy/radiation, surgery, transplant, or non-therapeutic (hospice, surveillance, or palliative care). Agreement between NGS test report targeted therapy recommendations based on the FDA variant classification and physician targeted therapy treatment recommendations were evaluated. RESULTS: Excluding variants contraindicating targeted therapy (i.e., KRAS or NRAS mutations), at least one variant with FDA level 1 companion diagnostic supporting evidence as the most actionable was identified in 14% of tests, with physicians most frequently recommending targeted therapy (48%) for patients with these results. This stands in contrast to physicians recommending targeted therapy based on test results with FDA level 2 (practice guideline) or FDA level 3 (clinical trial or off label) evidence as the most actionable result (11 and 4%, respectively). CONCLUSIONS: We found an appropriate "dose-response" relationship between the strength of clinical evidence supporting biomarker-directed targeted therapy based on application of FDA guidance for NGS test variant classification, and subsequent treatment recommendations made by treating physicians. In view of recent changes at FDA, it is paramount to define regulatory grounds and medical policy coverage for NGS testing based on this guidance.

Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer.

Using complete genome analysis, we sequenced five bladder tumors accrued from patients with muscle-invasive transitional cell carcinoma of the urinary bladder (TCC-UB) and identified a spectrum of genomic aberrations. In three tumors, complex genotype changes were noted. All three had tumor protein p53 mutations and a relatively large number of single-nucleotide variants (SNVs; average of 11.2 per megabase), structural variants (SVs; average of 46), or both. This group was best characterized by chromothripsis and the presence of subclonal populations of neoplastic cells or intratumoral mutational heterogeneity. Here, we provide evidence that the process of chromothripsis in TCC-UB is mediated by nonhomologous end-joining using kilobase, rather than megabase, fragments of DNA, which we refer to as "stitchers," to repair this process. We postulate that a potential unifying theme among tumors with the more complex genotype group is a defective replication-licensing complex. A second group (two bladder tumors) had no chromothripsis, and a simpler genotype, WT tumor protein p53, had relatively few SNVs (average of 5.9 per megabase) and only a single SV. There was no evidence of a subclonal population of neoplastic cells. In this group, we used a preclinical model of bladder carcinoma cell lines to study a unique SV (translocation and amplification) of the gene glutamate receptor ionotropic N-methyl D-aspertate as a potential new therapeutic target in bladder cancer.

SCNVSim: somatic copy number variation and structure variation simulator.

BACKGROUND: Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods. RESULTS: SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity. CONCLUSIONS: SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies.

MAC: identifying and correcting annotation for multi-nucleotide variations.

BACKGROUND: Next-Generation Sequencing (NGS) technologies have rapidly advanced our understanding of human variation in cancer. To accurately translate the raw sequencing data into practical knowledge, annotation tools, algorithms and pipelines must be developed that keep pace with the rapidly evolving technology. Currently, a challenge exists in accurately annotating multi-nucleotide variants (MNVs). These tandem substitutions, when affecting multiple nucleotides within a single protein codon of a gene, result in a translated amino acid involving all nucleotides in that codon. Most existing variant callers report a MNV as individual single-nucleotide variants (SNVs), often resulting in multiple triplet codon sequences and incorrect amino acid predictions. To correct potentially misannotated MNVs among reported SNVs, a primary challenge resides in haplotype phasing which is to determine whether the neighboring SNVs are co-located on the same chromosome. RESULTS: Here we describe MAC (Multi-Nucleotide Variant Annotation Corrector), an integrative pipeline developed to correct potentially mis-annotated MNVs. MAC was designed as an application that only requires a SNV file and the matching BAM file as data inputs. Using an example data set containing 3024 SNVs and the corresponding whole-genome sequencing BAM files, we show that MAC identified eight potentially mis-annotated SNVs, and accurately updated the amino acid predictions for seven of the variant calls. CONCLUSIONS: MAC can identify and correct amino acid predictions that result from MNVs affecting multiple nucleotides within a single protein codon, which cannot be handled by most existing SNV-based variant pipelines. The MAC software is freely available and represents a useful tool for the accurate translation of genomic sequence to protein function.

Cancer/testis antigen expression and co-expression patterns in Gastroesophageal Adenocarcinoma.

Gastroesophageal adenocarcinoma (GEAC) poses a significant challenge due to its poor prognosis and limited treatment options. Recently, Cancer/testis antigens (CTAs) have emerged as potential therapy targets due to their high expression in tumor cells and their immunogenic nature. We aimed to explore the expression and co-expression of CTAs in GEAC. We analyzed 63 GEAC patients initially and validated our findings in 329 patients from The Cancer Genome Atlas (TCGA) database. CTA expression was measured after RNA sequencing, while clinical information, including survival outcomes and treatment details, was collected from an institutional database. Co-expression patterns among CTAs were determined using Pearson correlation analysis. The majority of the study cohort were male (87%), Caucasian (94%), and had stage IV disease (64%). CTAs were highly prevalent, ranging from 58-19%. The MAGE gene family showed the highest expression, consistent across both cohorts. The correlation matrix revealed a distinct cluster of significantly co-expressed genes, including MAGEA3, NY-ESO-1, and others (0.27 ≤ r ≤ 0.73). Survival analysis revealed that individual CTAs were associated with poorer survival outcomes in patients not receiving immunotherapy while showing potential for improved survival in those undergoing immunotherapy, although these findings lacked robust reliability. Our study provides a comprehensive characterization of CTA expression and co-expression in GEAC. The strong correlation among CTAs like MAGE, NY-ESO-1, and GAGE suggests a potential for therapies targeting multiple CTAs simultaneously. Further research, including prospective trials, is warranted to assess the prognostic value of CTAs and their suitability as therapeutic targets.

High CTLA-4 transcriptomic expression correlates with high expression of other checkpoints and with immunotherapy outcome.

Background: CTLA-4 impedes the immune system's antitumor response. There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents. Objective: To assess the prognostic implications and immunologic correlates of high CTLA-4 in tumors of patients on immunotherapy and those on non-immunotherapy treatments. Design/methods: We evaluated RNA expression levels in a clinical-grade laboratory and clinical correlates of CTLA-4 and other immune checkpoints in 514 tumors, including 489 patients with advanced/metastatic cancers and full outcome annotation. A reference population (735 tumors; 35 histologies) was used to normalize and rank transcript abundance (0-100 percentile) to internal housekeeping gene profiles. Results: The most common tumor types were colorectal (140/514, 27%), pancreatic (55/514, 11%), breast (49/514, 10%), and ovarian cancers (43/514, 8%). Overall, 87 of 514 tumors (16.9%) had high CTLA-4 transcript expression (⩾75th percentile rank). Cancers with the largest proportion of high CTLA-4 transcripts were cervical cancer (80% of patients), small intestine cancer (33.3%), and melanoma (33.3%). High CTLA-4 RNA independently/significantly correlated with high PD-1, PD- L2, and LAG3 RNA levels (and with high PD-L1 in univariate analysis). High CTLA-4 RNA expression was not correlated with survival from the time of metastatic disease [N = 272 patients who never received immune checkpoint inhibitors (ICIs)]. However, in 217 patients treated with ICIs (mostly anti-PD-1/anti-PD- L1), progression-free survival (PFS) and overall survival (OS) were significantly longer among patients with high versus non-high CTLA-4 expression [hazard ratio, 95% confidence interval: 0.6 (0.4-0.9) p = 0.008; and 0.5 (0.3-0.8) p = 0.002, respectively]; results were unchanged when 18 patients who received anti-CTLA-4 were omitted. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy. Conclusion: High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

High CTLA-4 expression and immunotherapy outcome High CTLA-4 expression was not a prognostic factor for survival in patients not receiving ICIs but was a significant positive predictive biomarker for better outcome (PFS and OS) in patients on immunotherapy, perhaps because it correlated with expression of other checkpoints such as PD-1 and PD-L2.

LAG-3 transcriptomic expression correlates linearly with other checkpoints, but not with clinical outcomes.

Immune checkpoint inhibitors have revolutionized the treatment landscape for patients with cancer. Multi-omics, including next-generation DNA and RNA sequencing, have enabled the identification of exploitable targets and the evaluation of immune mediator expression. There is one FDA-approved LAG-3 inhibitor and multiple in clinical trials for numerous cancers. We analyzed LAG-3 transcriptomic expression among 514 patients with diverse cancers, including 489 patients with clinical annotation for their advanced malignancies. Transcriptomic LAG-3 expression was highly variable between histologies/cancer types and within the same histology/cancer type. LAG-3 RNA levels correlated linearly, albeit weakly, with high RNA levels of other checkpoints, including PD-L1 (Pearson's R2 = 0.21 (P < 0.001)), PD-1 (R2 = 0.24 (P < 0.001)) and CTLA-4 (R2 = 0.19 (P < 0.001)); when examined for Spearman correlation, significance did not change. LAG-3 expression (dichotomized at ≥ 75th (high) versus < 75th (moderate/low) RNA percentile level) was not a prognostic factor for overall survival (OS) in 272 immunotherapy-naïve patients with advanced/metastatic disease (Kaplan Meier analysis; P = 0.54). High LAG-3 levels correlated with longer OS after anti-PD-1/PD-L1-based checkpoint blockade (univariate (P = 0.003), but not multivariate analysis (hazard ratio, 95% confidence interval = 0.80 (0.46-1.40) (P = 0.44))); correlation with longer progression-free survival showed a weak univariate trend (P = 0.13). Taken together, these results suggest that high LAG-3 levels in and of themselves do not predict resistance to anti-PD-1/PD-L1 checkpoint blockade. Even so, since LAG-3 is often co-expressed with PD-1, PD-L1 and/or CTLA-4, selecting patients for combinations of checkpoint blockade based on immunomic co-expression patterns is a strategy that merits exploration.

High indoleamine 2,3-dioxygenase transcript levels predict better outcome after front-line cancer immunotherapy.

Indoleamine 2,3-dioxygenase 1 (IDO1), which catabolizes tryptophan, is a potential target to unlock the immunosuppressive tumor microenvironment. Correlations between IDO1 and immune checkpoint inhibitor (ICI) efficacy remain unclear. Herein, we investigated IDO1 transcript expression across cancers and clinical outcome correlations. High IDO1 transcripts were more frequent in uterine (54.2%) and ovarian cancer (37.2%) but varied between and within malignancies. High IDO1 RNA expression was associated with high expression of PD-L1 (immune checkpoint ligand), CXCL10 (an effector T cell recruitment chemokine), and STAT1 (a component of the JAK-STAT pathway) (all multivariable p < 0.05). PIK3CA and CTCF alterations were more frequent in the high IDO1 group. High IDO1 expression was an independent predictor of progression-free survival (adjusted HR = 0.44, 95% CI 0.20-0.99, p = 0.049) and overall survival (adjusted HR = 0.31, 95% CI 0.11-0.87, p = 0.026) after front-line ICIs. IDO1 expression warrants further exploration as a predictive biomarker for immunotherapy. Moreover, co-expressed immunoregulatory molecules merit exploration for co-targeting.

TIM-3 transcriptomic landscape with clinical and immunomic correlates in cancer.

TIM-3, an inhibitory checkpoint receptor, may invoke anti-PD-1/anti-PD-L1 immune checkpoint inhibitor (ICI) resistance. The predictive impact of TIM-3 RNA expression in various advanced solid tumors among patients treated with ICIs is yet to be determined, and their prognostic significance also remains unexplored. We investigated TIM-3 transcriptomic expression and clinical outcomes. We examined TIM-3 RNA expression data through the OmniSeq database. TIM-3 transcriptomic patterns were calibrated against a reference population (735 tumors), adjusted to internal housekeeping genes, and calculated as percentiles. Overall, 514 patients (31 cancer types; 489 patients with advanced/metastatic disease and clinical annotation) were assessed. Ninety tumors (17.5% of 514) had high (≥75th percentile RNA rank) TIM-3 expression. Pancreatic cancer had the greatest proportion of TIM-3 high expressors (36% of 55 patients). Still, there was variability within cancer types with, for instance, 12.7% of pancreatic cancers harboring low TIM-3 (<25th percentile) levels. High TIM-3 expression independently and significantly correlated with high PD-L2 RNA expression (odds ratio (OR) 9.63, 95% confidence interval (CI) 4.91-19.4, P<0.001) and high VISTA RNA expression (OR 2.71, 95% CI 1.43-5.13, P=0.002), all in multivariate analysis. High TIM-3 RNA did not correlate with overall survival (OS) from time of metastatic disease in the 272 patients who never received ICIs, suggesting that it is not a prognostic factor. However, high TIM-3 expression predicted longer median OS (but not progression-free survival) in 217 ICI-treated patients (P=0.0033; median OS, 2.84 versus 1.21 years (high versus not-high TIM-3)), albeit not retained in multivariable analysis. In summary, TIM-3 RNA expression was variable between and within malignancies, and high levels associated with high PD-L2 and VISTA checkpoints and with pancreatic cancer. Individual tumor immunomic assessment and co-targeting co-expressed checkpoints merits exploration in prospective trials as part of a precision immunotherapy strategy.

Transcriptomic analysis of GITR and GITR ligand reveals cancer immune heterogeneity with implications for GITR targeting.

Glucocorticoid-induced tumor necrosis factor related protein (GITR) is a transmembrane protein expressed mostly on CD25+CD4+ regulatory T-cells (Tregs) and upregulated on all T-cells upon activation. It is a T-cell co-stimulatory receptor and has demonstrated promising anti-tumor activity in pre-clinical studies. To date, however, the efficacy of GITR agonism has been discouraging in clinical trials. This study explores GITR and GITR ligand (GITR-L) ribonucleic acid (RNA) expression in solid tumors in an attempt to delineate causes for variable responses to GITR agonists. RNA expression levels of 514 patients with a variety of cancer types were normalized to internal housekeeping gene profiles and ranked as percentiles. 99/514 patients (19.3%) had high GITR expression (defined as ≥ 75th percentile). Breast and lung cancer had the highest proportion of patients with high GITR expression (39% and 35%, respectively). The expression of concomitant high GITR and low-moderate GITR-L expression (defined as <75th percentile) was present in 31% and 30% of patients with breast and lung cancer respectively. High GITR expression also showed a significant independent association with high RNA expression of other immune modulator proteins, namely, PD-L1 immunohistochemistry (IHC) ≥1 (odds ratio (OR) 2.15, P=0.008), CTLA4 (OR=2.17, P=0.05) and OX40 high RNA expression (OR=2.64, P=0.001). Overall, these results suggest that breast and lung cancer have a high proportion of patients with a GITR and GITR-L RNA expression profile that merits further investigation in GITR agonism studies. The association of high GITR expression with high CTLA4 and OX40 RNA expression, as well as positive PD-L1 IHC, provides a rationale for a combination approach targeting these specific immune modulator proteins in patients whose tumors show such co-expression.

The transcriptomic expression pattern of immune checkpoints shows heterogeneity between and within cancer types.

Transcriptomic expression profiles of immune checkpoint markers are of interest in order to decipher the mechanisms of immunotherapy response and resistance. Overall, 514 patients with various solid tumors were retrospectively analyzed in this study. The RNA expression levels of tumor checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) were ranked from 0-100 percentile based on a reference population. The expression of each checkpoint was correlated with cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) by immunohistochemistry (IHC). The cohort included 30 different tumor types, with colorectal cancer being the most common (27%). When RNA percentile rank values were categorized as "Low" (0-24), "Intermediate" (25-74), and "High" (75-100), each patient had a distinctive portfolio of the categorical expression of 16 checkpoint markers. Association between some checkpoint markers and cancer types were observed; NOS2 showed significantly higher expression in colorectal and stomach cancer (P < 0.001). Principal component analysis demonstrated no clear association between combined RNA expression patterns of 16 checkpoint markers and cancer types, TMB, MSI or PD-L1 IHC. Immune checkpoint RNA expression varies from patient to patient, both within and between tumor types, though colorectal and stomach cancer showed the highest levels of NOS2, a mediator of inflammation and immunosuppression. There were no specific combined expression patterns correlated with MSI, TMB or PD-L1 IHC. Next generation immunotherapy trials may benefit from individual analysis of patient tumors as selection criteria for specific immunomodulatory approaches.

Immunologic Factors Associated with Differential Response to Neoadjuvant Chemoimmunotherapy in Triple-Negative Breast Cancer.

Background: KEYNOTE-522 resulted in FDA approval of the immune checkpoint inhibitor pembrolizumab in combination with neoadjuvant chemotherapy for patients with early-stage, high-risk, triple-negative breast cancer (TNBC). Unfortunately, pembrolizumab is associated with several immune-related adverse events (irAEs). We aimed to identify potential tumor microenvironment (TME) biomarkers which could predict patients who may attain pathological complete response (pCR) with chemotherapy alone and be spared the use of anti-PD-1 immunotherapy. Methods: Comprehensive immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on matched FFPE tumor samples from 22 stage I-III TNBC patients (14 patients treated with neoadjuvant chemotherapy alone (NAC) and 8 treated with neoadjuvant chemotherapy combined with pembrolizumab (NAC+I)). Results: Differential gene expression analysis revealed that in the NAC group, IL12B and IL13 were both significantly associated with pCR. In the NAC+I group, LCK and TP63 were significantly associated with pCR. Patients in both treatment groups exhibiting pCR tended to have greater tumor inflammation than non-pCR patients. In the NAC+I group, patients with pCR tended to have greater cell proliferation and higher PD-L1 expression, while in the NAC group, patients with pCR tended to have lower cancer testis antigen expression. Additionally, the NAC+I group trended toward a lower relative dose intensity averaged across all chemotherapy drugs, suggesting that more dose reductions or treatment delays occurred in the NAC+I group than the NAC group. Conclusions: A comprehensive understanding of immunologic factors could potentially predict pCR to chemotherapy alone, enabling the avoidance of the unnecessary treatment of these patients with checkpoint inhibitors.

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.

Introduction: Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. Methods: We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. Results: We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. Discussion: These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.

The Impact of Prior Single-Gene Testing on Comprehensive Genomic Profiling Results for Patients with Non-Small Cell Lung Cancer.

INTRODUCTION: Tissue-based broad molecular profiling of guideline-recommended biomarkers is advised for the therapeutic management of patients with non-small cell lung cancer (NSCLC). However, practice variation can affect whether all indicated biomarkers are tested. We aimed to evaluate the impact of common single-gene testing (SGT) on subsequent comprehensive genomic profiling (CGP) test outcomes and results in NSCLC. METHODS: Oncologists who ordered SGT for guideline-recommended biomarkers in NSCLC patients were prospectively contacted (May-December 2022) and offered CGP (DNA and RNA sequencing), either following receipt of negative SGT findings, or instead of SGT for each patient. We describe SGT patterns and compare CGP completion rates, turnaround time, and recommended biomarker detection for NSCLC patients with and without prior negative SGT results. RESULTS: Oncologists in > 80 community practices ordered CGP for 561 NSCLC patients; 135 patients (27%) first had negative results from 30 different SGT combinations; 84% included ALK, EGFR and PD-L1, while only 3% of orders included all available SGTs for guideline-recommended genes. Among patients with negative SGT results, CGP was attempted using the same tissue specimen 90% of the time. There were also significantly more CGP order cancellations due to tissue insufficiency (17% vs. 7%), DNA sequencing failures (13% vs. 8%), and turnaround time > 14 days (62% vs. 29%) than among patients who only had CGP. Forty-six percent of patients with negative prior SGT had positive CGP results for recommended biomarkers, including targetable genomic variants in genes beyond ALK and EGFR, such as ERBB2, KRAS (non-G12C), MET (exon 14 skipping), NTRK2/3, and RET . CONCLUSION: For patients with NSCLC, initial use of SGT increases subsequent CGP test cancellations, turnaround time, and the likelihood of incomplete molecular profiling for guideline-recommended biomarkers due to tissue insufficiency.

Patients with non-small cell lung cancer (NSCLC) should have their tumor tissue tested for all recommended biomarkers that can help identify their best treatment options. Traditional tests look at gene biomarkers one by one (single-gene testing), and doctors can order some or all these tests individually or in a group. However, some recommended biomarkers cannot be tested by traditional single-gene tests at all. Newer technology (next-generation sequencing) covers all current recommended treatment biomarkers in one test (comprehensive genomic profiling), but this testing is more expensive and can take more time. Our study shows that NSCLC patients do not get all recommended treatment biomarkers tested when a single-gene testing approach is taken. Single-gene testing also used up some patients' tumor tissue entirely, such that further testing by comprehensive genomic profiling could not be done at all (17% vs. 7% for patients with no prior single-gene tests), resulted in more sequencing failures (13% vs. 8%), and had turnaround time for results greater than 14 days for more patients (62% vs. 29%). When comprehensive genomic profiling was completed, 46% of patients with negative results from prior single-gene testing had positive results for recommended treatment biomarkers that were not included in the initial single-gene tests. To ensure that NSCLC patients receive testing for all recommended biomarkers, comprehensive genomic profiling must be performed first.

Differential copy number aberrations in novel candidate genes associated with progression from in situ to invasive ductal carcinoma of the breast.

Only a minority of intraductal carcinomas of the breast give rise to stromally invasive disease. We microdissected 206 paraffin blocks representing 116 different cases of low-grade ductal carcinoma in situ (DCIS). Fifty-five were pure DCIS (PD) cases without progression to invasive carcinoma. Sixty-one cases had a small invasive component. DNA was extracted from microdissected sections and hybridized to high-density bacterial artificial chromosome arrays. Array comparative genomic hybridization analysis of 118 hybridized DNA samples yielded data on 69 samples that were suitable for further statistical analysis. This cohort included 20 pure DCIS cases, 25 mixed DCIS (MD), and 24 mixed invasive carcinoma samples. PD cases had a higher frequency of DNA copy number changes than MD cases, and the latter had similar DNA profiles compared to paired invasive carcinomas. Copy number changes on 13 chromosomal arms occurred at different rates in PD versus MD lesions. Eight of 19 candidate genes residing at those loci were confirmed to have differential copy number changes by quantitative PCR. NCOR2/SMRT and NR4A1 (both on 12q), DYNLRB2 (16q), CELSR1, UPK3A, and ST13 (all on 22q) were more frequently amplified in PD. Moreover, NCOR2, NR4A1, and DYNLRB2 showed more frequent copy number losses in MD. GRAP2 (22q) was more often amplified in MD, whereas TAF1C (16q) was more commonly deleted in PD. A multigene model comprising these candidate genes discriminated between PD and MD lesions with high accuracy. These findings suggest that the propensity to invade the stroma may be encoded in the genome of intraductal carcinomas.