Genomic Profiling Data Research Articles

Utility of Targeted Next Generation Sequencing (NGS) to Predict Hematologic Neoplasms with Germline Predisposition

Abstract Introduction/Objective Hematologic neoplasms with germline predisposition are increasingly gaining clinical relevance as associated gene variants are emerging. These variants confer an increased risk for developing hematologic neoplasms as additional somatic aberrations accumulate. Recognition of germline predisposition is crucial to patient management as it would prompt genetic counseling and regular surveillance in affected patients and biological family members, as well as guide therapy, as many patients undergo allogeneic stem cell transplantation for which relatives are typically the preferred donors. Furthermore, these patients may respond differently to conventional therapies. Clinical recognition of germline predisposition is challenging due to phenotypic heterogeneity and a lack of germline testing standards and resources. Next generation sequencing is routinely utilized to detect somatic variants associated with hematopoietic neoplasms. Molecular profiling may also potentially serve as a screening tool to suggest pathogenic germline variants. Methods/Case Report Comprehensive genomic profiling data was reviewed for 301 patients with known hematologic neoplasms. A somatic-germline-zygosity (SGZ) computational method classified variants by origin. Variants of unknown clinical significance were excluded. The final study showed 94 patients predicted to have germline variants. The variables analyzed include germline variants, concurrent mutations, diagnosis, sex, age, and ancestry. Results (if a Case Study enter NA) Acute myeloid leukemia was the most frequent diagnosis, followed by B-cell acute lymphoblastic leukemia, myeloproliferative neoplasms, myelodysplastic syndrome, and chronic myelomonocytic leukemia. The median patient age was 60 years, ranging from 6 months to 91 years. Male gender and European ancestry were proportionally greater. In this study, we identified 70 distinct genes with 145 germline pathogenic variants. The most common pathogenic germline variants were TET2, SRSF2, RUNX1, DNMT3A, and CHEK2. Conclusion In conclusion, SGZ computational methods can be used as a screening tool to predict possible germline mutations in hematologic malignancies, which will help guide treatment and improve patient and family outcomes

Genomic landscape of cutaneous, acral, mucosal, and uveal melanoma in Japan: analysis of clinical comprehensive genomic profiling data.

Cutaneous melanoma (CM) is the most common type in Caucasians, while acral melanoma (AM) and mucosal melanoma (MM), which are resistant to immunotherapies and BRAF/MEK-targeted therapies, are more common in East Asians. Genomic profiling is essential for treating melanomas, but such data are lacking in Japan. Comprehensive genomic profiling data compiled in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) were analyzed. A total of 380 melanomas was analyzed, including 136 CM, 46 AM, 168 MM, and 30 uveal melanoma (UM). MM included conjunctival, sinonasal, oral, esophageal, anorectal, and vulvovaginal melanomas. No significant difference in the median tumor mutational burden (TMB) of CM (3.39 mutations/megabase), AM (2.76), and MM (3.78) was the key finding. Microsatellite instability-high status was found in one case. BRAF V600E/K was found in only 45 patients (12%). Key driver mutations in CM were BRAF (38%), NRAS (21%), NF1 (8%), and KIT (10%), with frequent copy number alterations (CNAs) of CDKN2A, CDKN2B, and MYC. AM was characterized by altered KIT (30%), NRAS (26%), and NF1 (11%) and CDKN2A, CDKN2B, CDK4, MDM2, and CCND1 CNAs. MM was characterized by altered NRAS (24%), KIT (21%), and NF1 (17%) and MYC, KIT, and CDKN2A CNAs, with differences based on anatomical locations. UM bore GNAQ or GNA11 driver mutations (87%) and frequent mutations in SF3B1 or BAP1. The distinct genomic profiling in Japanese patients, including lower TMB, compared to Caucasians, is associated with poorer treatment outcomes. This result underscores the need for more effective therapeutic agents.

The impact of HRD mutation on survival in patients with KRAS-mutated advanced pancreatic cancer: A real-world database study.

221 Background: Advanced pancreatic ductal adenocarcinoma (PDAC) is associated with a poor prognosis. Prior studies indicate that homologous repair deficient (HRD+ve) PDAC patients (pts) have improved survival and greater response to platinum agents, but the optimal treatment for these population is still unclear. Here, we evaluate the survival impact of HRD mutations in KRAS-mutated PDAC, which represent 90% of cases, in a real-world setting. Methods: We retrospectively reviewed all pts diagnosed with KRAS-mutated PDAC from Jun 2019 to Dec 2021, who were registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), the cancer registry with comprehensive genomic profiling (CGP) data. Pts were stratified with the presence or absence of HRD mutations identified through Foundation One, including ATM, ATR, BRCA1, BRCA2, BRIP1, CHEK2, FANCA, PALB2, and RAD51. We analyzed the prevalence of co-alterations and the impact of HRD status on survival. Pts with a history of systemic therapy for curative intent were excluded from the survival analysis. Results: In 2251 PDAC cases (HRD+ve 232pts, HRD-ve 2019pts) enrolled, we found that HRD+ve PDAC had a significantly lower incidence of TP53 mutation (p<0.001), CDKN2A mutation (p<0.046), and CDKN2A loss (p<0.046). Survival analysis was performed in 823 pts (HRD+ve 92pts, HRD-ve 731pts). HRD+ve pts had significantly longer overall survival (OS, 28.8m vs 23.5m, P=0.030). In the first line setting, HRD+ve pts had exhibited a markedly extended time-to-treatment failure (TTF; [HRD+ve, 19pts vs. HRD-ve, 177pts]; 7.6m vs. 5.4m; p=0.026) and OS ([HRD+ve, 30pts vs. HRD-ve, 239pts]; 28.8m vs. 23.5m; p=0.019) when treated with mFOLFIRINOX (mFFX), but not when treated with gemcitabine plus nab-paclitaxel (GA; [HRD+ve, 34pts vs. HRD-ve 276pts]; OS, 29.3m vs 26.3m; p=0.34; TTF, 5.2m vs. 5.2m; p=0.80). In the second line setting, there were no differences in TTF between HRD+ve and HRD-ve irrespective of these regimens. Among HRD+ve PDAC pts, pts who having received mFFX tend to have better survival compared to those who did not (46pts vs. 46pts; OS, 31.7m vs 26.3m; p=0.09). Conclusions: Our analysis has identified a unique profile in HRD+ve PDAC, underscoring the importance of platinum-based chemotherapy in the initial treatment to enhance survival, which highlights the practical clinical benefits of routine CGP for pts with KRAS-mutated PDAC.

DIPG-14. METABOLIC REPROGRAMMING AS A RESISTANCE MECHANISM IN DIFFUSE MIDLINE GLIOMA

Abstract BACKGROUND Diffuse midline gliomas (DMG) are uniformly fatal pediatric brain cancers, refractory to current standards of care. Based on genomic and transcriptomic profiling data, we previously proposed that platelet-derived growth factor receptor alpha (PDGFRA) is crucial to the tumorigenic potential and maintenance of stem-like DMG cells and that targeting PDGFRA is an important therapeutic avenue in DMG. In comprehensive pre-clinical studies, we identified avapritinib, an FDA-approved PDGFRA inhibitor, to be highly effective in patient-derived xenograft (PDX) DMG models. We further reported the first clinical experience using avapritinib in recurrent DMG and demonstrated preliminary safety, tolerability, and efficacy of the drug in this population. While a subset of patients experienced a strong clinical response from avapritinib, tumor progression was eventually observed in all patients. METHODS Here, we investigated the molecular mechanisms that DMG cells upregulate following avapritinib treatment, with the aim to exploit them therapeutically. To uncover these mechanisms, we performed transcriptomic, metabolic and functional assays along with a combinatorial drug screening. RESULTS Transcriptional analysis of patient-derived DMG cell lines revealed an upregulation of genes associated with fatty acid metabolism and oxidative phosphorylation (OXPHOS) following treatment with avapritinib. Functional assays confirmed elevated OXPHOS in avapritinib-treated cells with significant (i) increase in mitochondrial energy transduction, (ii) increase in palmitate- (a product of fatty acid metabolism) driven oxygen consumption rate and (iii) greater incorporation of palmitate-derived carbons into the tricarboxylic acid cycle. To determine which therapies could target this dependency on OXPHOS and fatty acid metabolism, we performed a metabolic drug screening in patient-derived DMG cell lines and identified two metabolic drugs to have synergistic cytotoxic effects with avapritinib. CONCLUSION We revealed distinct metabolic reprogramming in avapritinib-treated DMG cells and showed that targeting these metabolic vulnerabilities might further increase the clinical benefit of PDGFRA inhibitor avapritinib.

Comprehensive genomic profiling from C-CAT database unveiled over 80% presence of oncogenic drivers in anaplastic thyroid carcinoma including BRAF, RAS family, NF1, and FGFR1.

Anaplastic thyroid carcinoma (ATC) is considered a very aggressive carcinoma and has been difficult to treat with therapeutic strategies. This study examines the landscape of genomic alteration in ATC, including the BRAF V600E mutation, and its clinical implications. A retrospective observational study was conducted using collected at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) in Japan, utilizing comprehensive genomic profiling data from 102 ATC cases. Additionally, AACR-GENIE data from 267 cases were analysed for validation. Statistical methods, including the conditional Kendall tau statistic and χ2 tests, were employed for survival analysis and gene mutation comparisons. Among 102 ATCs, BRAF, RAS, and other driver mutations were found in 83 cases (81.2%). The prevalence of BRAF V600E mutations was as high as 60%. Co-mutation analysis identified different genomic profiles in the BRAF, RAS, and wild-type groups. Despite the diverse molecular backgrounds, no significant differences in clinical variables and overall survival were observed. The analysis considering left-side amputation suggested that RAS mutations had a poorer prognosis. In the BRAF/RAS wild-type group, FGFR1 and NF1 were identified as driver mutations, with an accumulation of copy number variations and less TERT promoter mutations. This molecular subgrouping was also supported by the AACR-GENIE data. Comprehensive genomic analysis of ATC in Japan revealed distinct molecular subgroups, highlighting the importance of BRAF V600E mutations, particularly V600E, as potential therapeutic targets and suggest the relevance of tailor-made therapeutic strategies based on genomic profiling.

Efficacy of immunotherapy in ARID1A-mutant solid tumors: a single-center retrospective study

BackgroundImmune checkpoint inhibitors (ICIs), especially those targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), have introduced a new treatment landscape for many types of tumors. However, they only achieve a limited therapeutic response. Hence, identifying patients who may benefit from ICIs is currently a challenge.Methods47 tumor patients harboring ARID1A mutations were retrospectively studied. The genomic profiling data through next-generation sequencing (NGS) and relevant clinical information were collected and analyzed. Additionally, bioinformatics analysis of the expression of immune checkpoints and immune cell infiltration levels was conducted in ARID1A-mutant gastric cancer (GC).ResultsARID1A mutations frequently co-occur with mutations in DNA damage repair (DDR)-associated genes. Among the 35 ARID1A-mutant patients who received immunotherapy, 27 were evaluable., with the objective response rate (ORR) was 48.15% (13/27), and the disease control rate (DCR) was 92.59% (25/27). Moreover, survival assays revealed that ARID1A-mutant patients had longer median overall survival (mOS) after immunotherapy. In ARID1A-mutated GC patients, receiving ICIs treatment indicated longer progressive-free survival (PFS). Additionally, the incidence of microsatellite instability-high (MSI-H), high tumor mutation burden (TMB-H) and Epstein‒Barr virus (EBV) infection was elevated. Bioinformatic analysis showed significant enrichment of immune response and T cell activation pathway within differentially expressed genes in ARID1A-mutant GC group. Finally, ARID1A mutations status was considered to be highly correlated with the level of tumor infiltrating lymphocytes (TILs) and high expression of immune checkpoints.ConclusionsPatients with tumors harboring ARID1A mutations may achieve better clinical outcomes from immunotherapy, especially in GC. ARID1A mutations can lead to genomic instability and reshape the tumor immune microenvironment (TIME), which can be used as a biomarker for immunotherapy.

Exploring the significance of MET overexpression by gene expression profiling versus immunohistochemistry in an EGFR-mutant lung cancer cohort.

e20600 Background: Amivantamab, an innovative EGFR-MET bispecific antibody, approved for use in EGFR exon 20 mutated lung cancers, recently demonstrated substantial clinical benefits in advanced/metastatic lung cancers with EGFR exon 19 deletion and/or L858R mutation according to data from the MARIPOSA clinical trial. Recent findings from the CHRYSALIS 2 trial indicate a potential role for MET overexpression as a predictive biomarker for response to Amivantamab combination therapy, particularly in cases resistant to Osimertinib. Methods: We retrospectively analyzed genomic profiling data in a large lung cancer cohort to characterize EGFR mutations. Additionally, we assessed MET expression via gene expression profiling (GEP) in a smaller EGFR-mutation positive sub-cohort to explore its prevalence. Results: Genomic profiling data from 799 tissue samples was included in our analysis. EGFR mutations were detected in 36%; higher prevalence of EGFR mutations was noted in our cohort (36%) vs the TCGA cohort (26%). Consistent with other studies, exon 19 deletion was the most frequent category of EGFR mutations (46%,), with EGFR p.E746_750del being the most frequent variant among them (60%). Exon 21 L858R mutation was the next most frequently detected variant (28%). Uncommon EGFR mutations were identified in 26% samples, with G719X being the most frequent among these. EGFR Exon 20 insertions contributed 6% of the EGFR variants. EGFR amplification was detected in 4.6% of samples. Of particular significance was the analysis of 21 EGFR-mutated tissue samples for targeted transcriptome analysis as a part Exacta Encyclopedic Tumor Analysis. The MET gene overexpression was detected in 52% of these samples. MET overexpression based on differential GEP identified a higher positivity rate than previously reported using MET immunohistochemistry (IHC) expression (52% vs. 36%), suggesting that GEP may be useful in identifying more patients with MET overexpression. This finding underscores the potential value of MET GEP as a biomarker, especially considering emerging data suggesting MET overexpression as a predictor for enhanced clinical benefit from the combination of Amivantamab and Lazertinib in EGFR-mutated, Osimertinib resistant patients. Furthermore, ongoing clinical trials are exploring MET overexpression as a biomarker for Amivantamab monotherapy. Conclusions: In conclusion, our study not only characterizes the landscape of EGFR mutations in a large lung cancer cohort but also highlights the prevalence of MET overexpression in EGFR-mutated samples, suggesting that MET GEP may serve as a promising predictive biomarker for enhanced clinical outcomes from Amivantamab therapy. In view of small sample size, further exploration and validation of MET overexpression by GEP is warranted in the context of EGFR-mutated advanced lung cancer.

Biomarker development from functional precision medicine datasets via explainable machine learning.

10061 Background: Genomics precision medicine, deployed via tumor panel sequencing, now assists in deploying targeted therapies to cancer patients. Numerous clinical trials have investigated the utility and benefit of genomics precision medicine in multiple cancer indications. Current large-scale studies report actionability rates from ~35% to ~60%, although clinical benefit rates have been shown to be closer to 10%. While this has positively impacted patients in need, the gap between actionability and benefit remains a clinical challenge attributed to multiple factors including the complex, multi-factorial relationship between molecular status and response to therapy. These differences go beyond simple disease states and may be reflective of multiple clinically relevant features including age, sex, and race/ethnicity. Methods: We implemented a functional precision medicine (FPM) program where patients with advanced pediatric cancers were prospectively profiled via high-throughput drug sensitivity testing (DST) of FDA-approved agents on patient-derived tumor cells as well as genomics testing. The objective was to investigate the clinical utility and benefit of FPM guidance in the treatment of pediatric cancer and elucidate the relationship between molecular status of patients’ diseases and treatment responses. We generated DST data (n = 21 patients) and genomic profiling data (n = 20 patients) on pediatric cancer patients in Miami, FL, as well as post-hoc whole exome and transcriptome sequencing data (n = 13 patients) and investigated three specific relationships. Results: We analyzed the relationship between racial/ethnic background and functional response to anti-cancer agents, determining potential differences in response to therapeutic classes. Next, we examined relationships between functional response and cancer type, identifying an unanticipated lack of clustering between disease indications in patients with advanced pediatric cancers. Finally, we applied an explainable machine learning (xML) framework to the functional genomic dataset to develop multi-omics biomarker hypotheses for the chemotherapy agent idarubicin, pinpointing a potential multi-cancer relationship between response to idarubicin and known disease mechanisms in acute myeloid leukemia (AML), the sole indication where idarubicin is approved. We further present additional proof-of-concept studies generating biomarker hypotheses via xML, demonstrating a framework for development of multi-omics biomarkers. Conclusions: We are now expanding our pan-pediatric cancer functional genomics dataset through an NIMHD-funded expansion cohort (NCT05857969, n = 65 patients) to further investigate multi-omics relationships between functional and molecular characteristics and understand the role of race/ethnicity in the complex relationship.

Comprehensive characterization of ERBB2 genomic alterations inlung cancer.

3148 Background: ERBB2mutations () occur in 1-4% of non-small cell lung cancers (NSCLC). Trastuzumab-deruxtecan is FDA-approved for the treatment of metastatic ERBB2-mutant NSCLC based mostly on data from NSCLCs harboring tyrosine kinase domain (TKD) ERBB2mut. The genomic and clinical characteristics of NSCLC with ERBB2 mut beyond the TKD remain largely unexplored. Methods: Patients (pts) with NSCLCs with oncogenic ERBB2 mut and genomic tumor profiling data from the AACR Project GENIE database were included. The cohort was divided into pts with tumors harboring TKD, extracellular (ECD), or transmembrane (TMD) and juxtamembrane domain (JMD) ERBB2mut. Clinico-genomic characteristics were compared between the groups. The Kaplan-Meier method was used to estimate progression-free survival (PFS) with first-line systemic therapy, and log-rank tests were used for comparisons. Results: Of 483 pts with ERBB2-mutant NSCLC, 64% were female, 81% were White, and 13% were Asian. TKD, ECD, and TMD/JMD ERBB2 mut were identified in 362 (75%), 88 (18%), and 33 (7%) cases, respectively. Pts with ECD vs. TKD ERBB2mut tumors were more likely to be males (47% vs. 33%, p=0.03) and have tumors with squamous histology (7% vs. 1%, p<0.0001). Among pts with (n=39), those with ECD vs. TKD ERBB2 mut tumors were more likely to have a history of smoking (100% vs. 42%, p = 0.02). The most common TKD, ECD, and TMD/JMD ERBB2 mut were in-frame ex20ins Y772_A775dup (n=224/362, 62%), missense S310F/Y (n=45/88, 51%), and missense V659E/D (n=10/33, 30%) mut, respectively. ECD vs. TKD ERBB2-mutant tumors harbored a distinct genomic phenotype with significantly higher median tumor mutational burden (11.1 vs. 5.2 mut/Mb, p<0.003), median fraction of genome altered (0.2 vs. 0.1, p = 0.02), and rate of co-mut in EGFR (32% vs. 3.6%, p<0.0001), KRAS (17% vs. 2.5%, p<0.0001), STK11 (23% vs. 4.3%, p<0.0001), KEAP1 (23% vs 5%, p<0.0001) and SMARCA4 (19% vs 4.5%, p<0.0001). Of 343 cases with ERBB2 copy number profiling, 32 (9.3%) harbored ERBB2 amplification. ERBB2-mutant NSCLCs with vs. without ERBB2amplifications had a higher frequency of TP53 co-mut (84% vs. 48%, p <0.001). Of 39 pts with available clinical data, most had ECD (n=6) ERBB2 mut tumors and received first-line platinum-based chemotherapy (n=31). The presence of a co-mut in STK11 (HR 3.5, 0.4–27.4, p=0.03) and KEAP1 (HR 3.9, 0.7–20.6, p=0.002) conferred shorter PFS on first-line systemic therapy. Pts with ECD vs. TKD ERBB2 mut tumors had shorter PFS (HR 2.4, 95% CI 0.7–8.2, p=0.04). Conclusions: NSCLC tumors harboring ECD ERBB2 mut are associated with a distinct clinical and molecular phenotype and inferior outcomes with chemotherapy compared to pts with tumors harboring TKD mut. These findings enhance our understanding of disease heterogeneity in ERBB2-mutant NSCLC and may aid in optimizing treatment strategies for this unique population.

A retrospective machine learning–based analysis of nationwide cancer comprehensive genomic profiling data to identify features associated with recommendation of mutation-based therapy.

e13510 Background: Comprehensive genomic profiling (CGP) has played key roles in cancer precision medicine through optimization of therapeutic interventions based on genomic alterations in cancer cells. However, the probability of discovering mutation-based treatments through CGP remains low. To enhance the effectiveness and efficiency of cancer precision medicine, it is crucial to identify patients who are likely to benefit from CGP tests. This study aims to identify characteristics of patients in which mutation-based treatments are discovered by CGP tests. Methods: We retrospectively analyzed data from 60,655 patients who underwent CGP tests and were registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), the national data center for cancer CGP in Japan. The C-CAT database covers 99.7% of cancer patients who have undergone CGP tests in Japan. Major cancer types included 10,182 cases of bowel cancer, 8,691 pancreas cancer, 5,062 biliary tract cancer, and 3,777 breast cancer. We developed an eXtreme Gradient Boosting (XGBoost) model using machine learning, and used clinical information as input to predict whether one or more Japanese Pharmaceuticals and Medical Devices Agency (PMDA)-approved drugs are discovered through CGP tests or not. Shapley Additive Explanations (SHAP) was employed to extract significant features that contribute to the model prediction. Results: The prediction model achieved an area under the receiver operating characteristic curve of 0.826 for the overall cancer population. Positive SHAP values were observed for patients with breast (mean SHAP in breast cancer patients: 1.38), lung (1.08), bowel (0.75), and pancreas cancers (0.35), while negative SHAP values were associated with head and neck (-1.75), cervical cancers (-1.54), and brain (-1.33). Positive SHAP values were also associated with presence of liver or lymph node metastasis (0.23, 0.08), shorter intervals between diagnosis and CGP testing or specimen collection and CGP testing, and advanced age. Similar trends were observed in cancer-type-specific prediction models, which also identified their own unique features. In the adolescent and young adult (AYA) age group, primary brain tumors were strongly associated with negative SHAP values (-1.37). Conclusions: Our machine learning-based analysis of nationwide CGP data identified features that predict cases in which mutation-based treatments are discovered by CGP tests, both in the overall cancer population and within specific cancer types and the AYA age group. Expedited CGP testing is recommended for patients who match the identified profile to facilitate early targeted therapy interventions.

Genomics to select treatment for patients (pts) with metastatic cancer: Final analysis of Molecular Tumor Board (MTB) evaluations in the ROME trial.

3157 Background: The ROME trial (NCT04591431) investigates the efficacy of a tailored treatment (TT), driven by extensive genomic tests and Molecular Tumor Board (MTB) evaluation, compared to standard treatment (SoC) in patients (pts) with refractory metastatic cancer. Here we report the prevalence of actionable variants identified and the personalized treatment received by the patients enrolled. Methods: A centralized extensive NGS test (FoundationOne CDx and Liquid CDx) was performed on both tissue and blood samples. Pts with at least one potentially targetable alteration matched to the available drugs were discussed at the MTB. MTB evaluation criteria were: genomic variant type, tumor mutational burden (TMB), VAF, availability of preclinical or clinical data of efficacy and patients’ clinical characteristics. COSMIC, ClinVar, OncoKB and VarSome datasets were used to evaluate the clinical actionability of genomic alterations. MTB indications were: randomization to TT vs SoC, screening failure (SF), or indication to other trial/access to the drug. Results: From November 2020 to August 2023, 1794 pts were screened. A total of 127 weekly MTB meetings were conducted and 899 cases were discussed (7 cases/meeting on average). After MTB discussion, a targetable genomic alteration was identified in 425 pts, who received an indication to be randomized. MTB assigned ICIs to 190 pts (155 to ipilimumab plus nivolumab; 8 to nivolumab) due to high (≥10 mut/mb) TMB. 234 pts had indications to target therapy: 86 pts (37%) to PI3K/AKT/mTOR inhibitors(i), 59 (25%) anti-HER2 agents, 34 (15%) FGFRi, 31 (13%) BRAF/MEKi, 7 (3%) PARPi, 5 (2%) CDK4/6i, 4 (2%) ALKi, 2 (>1%) NTRKi, 2 (>1%) RETi, 2 (>1%) Hedgehog-i, 1 (>1%) JAKi, 1 (>1%) MEKi. 27 pts had indication to ICIs plus target therapy combinations. Additionally, 150 pts with potentially hereditary variants were addressed to genetic counselling and germline testing. Finally, according to the genomic evaluation, 63 pts were referred by MTB to other clinical trial even if considered SF for the ROME trial, 34 patients received from the MTB a modification of the initially proposed standard therapy and 4 had both suggestions. Overall, 652 pts (36%) received an indication following NGS test and MTB evaluation. Conclusions: Our study provides evidence that MTB discussion of comprehensive genomic profiling data identifies a personalized treatment in a large (36%) fraction of patients, thus outperforming the traditional histological approach. Clinical trial information: NCT04591431 .

Impact of Genomic Alterations on Efficacy of Trastuzumab Deruxtecan Against Human Epidermal Growth Factor Receptor-2-Positive Advanced Gastric Cancer.

The impact of genomic alterations on response and resistance to trastuzumab deruxtecan (T-DXd) has not been elucidated. Thus, we sought to identify factors predicting sensitivity to T-DXd in gastric or gastroesophageal junction (G/GEJ) cancer. We conducted a retrospective study using real-world clinical data and next-generation sequencing-based comprehensive genomic profiling (CGP) data from patients with advanced G/GEJ cancers, collected by the nationwide database in Japan. We analyzed the associations between genomic alterations and the patients' survivals after T-DXd treatment. In 114 patients with human epidermal growth factor receptor-2 (HER2)-positive G/GEJ cancer treated with T-DXd, the most frequently altered genes were TP53 (82%), ERBB2 (80%), and CCNE1 (36%). Multivariate Cox regression analysis revealed CCNE1 amplification to be a significant predictor of shorter progression-free survival (PFS) after T-DXd treatment among 91 patients whose CGP samples were obtained before T-DXd (median PFS, 131 days v 189 days; hazard ratio [HR], 1.90 [95% CI, 1.02 to 3.53]; P = .044). Analyses of 1,450 G/GEJ cancers revealed significant CCNE1/ERBB2 coamplification (41% relative to 11% CCNE1 amplification in ERBB2-nonamplified tumors; P < .0001). ERBB2-activating mutations were also detected in 3.7% of G/GEJ cancers and in 8.8% of HER2-positive G/GEJ cancers treated with T-DXd. Patients with ERBB2-mutated tumors showed shorter PFS than those without ERBB2 mutations after T-DXd treatment (mPFS, 105 v 180 days; P = .046). CCNE1 amplification may confer primary resistance to T-DXd in HER2-positive G/GEJ cancer, suggesting that the cell cycle could be a potential therapeutic target in CCNE1/ERBB2 coamplified tumors. ERBB2-activating mutation may also attenuate T-DXd efficacy in HER2-positive G/GEJ cancer.

Cancercelllines.org-a novel resource for genomic variants in cancer cell lines.

Cancer cell lines are an important component in biological and medical research, enabling studies of cellular mechanisms as well as the development and testing of pharmaceuticals. Genomic alterations in cancer cell lines are widely studied as models for oncogenetic events and are represented in a wide range of primary resources. We have created a comprehensive, curated knowledge resource-cancercelllines.org-with the aim to enable easy access to genomic profiling data in cancer cell lines, curated from a variety of resources and integrating both copy number and single nucleotide variants data. We have gathered over 5600 copy number profiles as well as single nucleotide variant annotations for 16 000 cell lines and provide these data with mappings to the GRCh38 reference genome. Both genomic variations and associated curated metadata can be queried through the GA4GH Beacon v2 Application Programming Interface (API) and a graphical user interface with extensive data retrieval enabled using GA4GH data schemas under a permissive licensing scheme. Database URL: https://cancercelllines.org.

Diffuse Pleural Mesotheliomas with Genomic Near-Haploidization: A Newly Recognized Subset with Distinct Clinical, Histologic, and Molecular Features.

Diffuse pleural mesotheliomas (DPM) with genomic near-haploidization (GNH) represent a novel subtype first recognized by The Cancer Genome Atlas project; however, its clinicopathologic and molecular features remain poorly defined. We analyzed clinical genomic profiling data from 290 patients with DPM using the Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) assay. Allele-specific copy number analysis was performed using the Fraction and Allele-Specific Copy Number Estimates from Tumor Sequencing (FACETS) algorithm. A total of 210 patients were evaluable for loss of heterozygosity (LOH) analysis using FACETS from MSK-IMPACT tumor:normal sequencing data. In this cohort, GNH, defined as LOH across >80% of the genome, was detected in 10 cases (4.8%). Compared with non-GNH tumors, GNH DPMs were associated with younger age and less frequent self-reported history of occupational asbestos exposure. Histologically, GNH DPMs were enriched in biphasic subtype (80% vs. 14.5%) and showed abundant tumor-infiltrating lymphocytes (TILs). Genomic analysis revealed a higher frequency of TP53 alterations, whereas SETDB1 mutations were present in nearly all and only in this subset. The clinicopathologic and molecular findings were further validated in a separate cohort. Despite the younger age, patients with GNH DPMs had a shorter overall survival (10.9 vs. 25.4 months, P = 0.004); the poor prognostic impact of GNH remained significant after controlling for biphasic histology. Of three patients with GNH DPMs who received immune checkpoint blockade, two achieved a clinician-assessed partial response. GNH defines an aggressive subtype of mainly biphasic DPMs in younger patients with recurrent alterations in SETDB1 and TP53. The enrichment in biphasic histology and TILs, together with our preliminary immune checkpoint blockade response data and anecdotal clinical trial data, suggests that further evaluation of immunotherapy may be warranted in this subset.

Molecular insights from comprehensive genomic profiling data in advanced metastatic colorectal cancer in South Asian population: A retrospective observational study

ABSTRACT Background: An increase in colorectal cancer incidence has been reported in India, often presenting in advanced stages and resulting in poor survival. However, the genomic and therapeutic landscape is not well understood. Objective: The primary objective of the study was to understand the mutational profile of metastatic colorectal cancer in the Southeast Asian cohort, and the secondary objective was to define the proportion of patients with therapeutically significant variants. Materials and Methods: This retrospective study was conducted between January 2021 and September 2023, at 4baseCare Onco Solutions Pvt. Ltd., Bengaluru, Karnataka, India. Comprehensive genomic profiling (CGP) and biomarker testing for MSI, TMB, and PD-L1 was carried out in 477 metastatic advanced (Stage III/IV) colorectal cancer patients, for the current retrospective-observational study. Results: With CGP, we identified drivers/clinically actionable variants in 78.6% of the cohort (375 patients). Although 30.8% of our cohort (147 patients) was eligible to available targeted therapy, 29.5% (141 patients) were found to harbor variants imparting therapeutic resistance. The combined mutation frequency of APC, TP53, and KRAS was &gt;50%, while KRAS constituted &gt;90% of all RAS mutations. The mismatch repair (MMR) genes including MLH1, MLH3, MSH3, and POLE were exclusively found in colon cancers. Genomic alterations in several genes of prognostic/therapeutic significance were seen (mutations in PIK3CA, SMAD4, BRAF, and amplifications in KRAS, EGFR, and ERBB2). Of those tested, 15.8% (41 patients) of the cohort had high tumor mutation burden (TMB-H), 14% had high microsatellite instability (MSI-H) (46 patients), and 26.8% were programmed death-ligand 1 (PD-L1) positive (30 patients). Conclusion: Our study shows that CGP is an advantageous option for identifying subsets of patients eligible for various targeted therapies, thus, improving patient outcomes.

Lipidomic-Based Approach to 10 s Classification of Major Pediatric Brain Cancer Types with Picosecond Infrared Laser Mass Spectrometry.

Picosecond infrared laser mass spectrometry (PIRL-MS) is shown, through a retrospective patient tissue study, to differentiate medulloblastoma cancers from pilocytic astrocytoma and two molecular subtypes of ependymoma (PF-EPN-A, ST-EPN-RELA) using laser-extracted lipids profiled with PIRL-MS in 10 s of sampling and analysis time. The average sensitivity and specificity values for this classification, taking genomic profiling data as standard, were 96.41 and 99.54%, and this classification used many molecular features resolvable in 10 s PIRL-MS spectra. Data analysis and liquid chromatography coupled with tandem high-resolution mass spectrometry (LC-MS/MS) further allowed us to reduce the molecular feature list to only 18 metabolic lipid markers most strongly involved in this classification. The identified 'metabolite array' was comprised of a variety of phosphatidic and fatty acids, ceramides, and phosphatidylcholine/ethanolamine and could mediate the above-mentioned classification with average sensitivity and specificity values of 94.39 and 98.78%, respectively, at a 95% confidence in prediction probability threshold. Therefore, a rapid and accurate pathology classification of select pediatric brain cancer types from 10 s PIRL-MS analysis using known metabolic biomarkers can now be available to the neurosurgeon. Based on retrospective mining of 'survival' versus 'extent-of-resection' data, we further identified pediatric cancer types that may benefit from actionable 10 s PIRL-MS pathology feedback. In such cases, aggressiveness of the surgical resection can be optimized in a manner that is expected to benefit the patient's overall or progression-free survival. PIRL-MS is a promising tool to drive such personalized decision-making in the operating theater.

Abstract 17570: Combining Genomic Profiling and Clinical Data Through Machine Learning Modeling for the Prediction of Coronary Artery Disease Severity: Insights From the Genetic SYNTAX Score (GESS) Trial

Background: Genomic profiling emerges as a powerful partner in the prediction of CAD development. Hypothesis: Machine learning (ML) algorithms integrating genomic profiling and clinical data could improve patient outcomes by contributing to earlier non-invasive diagnosis of obstructive CAD. Aims: The Genetic Syntax Score (GESS) prospective cohort study aimed to create a ML-algorithm able to predict the severity of CAD based on the analysis of 228 single nucleotide polymorphisms (SNPs) and relevant clinical and demographic data. Ultimate goal of this analysis was to compare the predictive capacity of a SNP-including model with that of a clinical model without SNPs. Methods: Patients with suspected CAD (n=919, mean age: 64±12 years) underwent invasive coronary angiography (from 2019 to 2021), and, thereby, their SYNTAX score was determined. Peripheral blood samples were drawn for genomic profiling (next generation sequencing analysis of a custom-made panel consisting of 228 SNPs) under standardized methods. After the ML-based selection of the most important subset of features (clinical/SNPs), two competing meta-learners were fitted, called Model A (including clinical/demographic predictors) and Model B (Model A plus SNPs predictors). The difference in their predictive capacities for the precise assessment of CAD risk (whether a patient presents with SYNTAX score &gt;0 or =0) and CAD severity (whether a patient presents with higher SYNTAX score) was investigated via Delong’s test and Wilcoxon signed-rank test, respectively. Results: Our ML-algorithm identified a total of 8 SNPs (rs11984041, rs41291556, rs2023938, rs2107595, rs216172, rs1800562, rs3732379, and rs964184) as significant predictors of CAD risk, and 7 SNPs (rs4845625, rs6689306, rs2046934, rs1332844, rs6801273, rs663129, and rs870142) as significant predictors of CAD severity. Model B demonstrated superior performance compared to Model A (Z=2.451, p=0.014 for CAD risk assessment, and V=16731, p=0.002 for CAD severity assessment). Conclusion(s): The combined use of clinical/demographic parameters and genomic profiling might be deployed to improve the prediction of CAD risk and severity under the guidance of ML-techniques. Registration: NCT03150680

Vesical Imaging-Reporting and Data System use predicting the outcome of neoadjuvant pembrolizumab in muscle-invasive bladder cancer.

To evaluate the predictive capability of the pre- and post-pembrolizumab Vesical Imaging-Reporting and Data System (VI-RADS) to identify ypT0N0 or ypT≤1N0 response in muscle-invasive bladder cancer (MIBC) within the PURE-01 trial (ClinicalTrials.gov identifier: NCT02736266). Patients were staged with bladder multiparametric magnetic resonance imaging (mpMRI) before and after treatment (three cycles of pembrolizumab) prior to radical cystectomy (RC). Logistic regression models were used to analyse the pre- and post- pembrolizumab VI-RADS against ypT≤1N0 and ypT0N0 response. The VI-RADS scores were dichotomised between 0 and 3 (0 = no evidence of disease) and 4-5. Event-free survival (EFS) and overall survival (OS) analyses were performed. Comprehensive genomic profiling and transcriptome-wide expression profiling data were matched with the VI-RADS scores. In total, 110 patients underwent centrally reviewed scans (N = 220 mpMRI), treated between February 2017 and July 2020. Both pre- and post-pembrolizumab VI-RADS 0-3 scores were the only significant covariates that predicted the ypT≤1N0 endpoint in multivariable analyses, and the strongest effect was seen with post-pembrolizumab VI-RADS 0-3 predicting the ypT≤1N0 response (P < 0.001). The area under the curve for this model was 0.90. Post-pembrolizumab VI-RADS 0-3 also predicted a longer EFS (P < 0.001) and OS (P = 0.044). The scores of several gene signatures from baseline tumours differed between the pre-pembrolizumab VI-RADS 0-3 and 4-5 categories. Post-pembrolizumab VI-RADS scores are strongly associated with pathological downstaging and survival. VI-RADS scores were also characterised by distinct biomarker features. These results indicate that the VI-RADS is emerging as an important tool for designing next-generation trials for MIBC.

Molecular features and clinical implications of the heterogeneity in Chinese patients with HER2-low breast cancer

The molecular heterogeneity and distinct features of HER2-low breast cancers, particularly in the Chinese population, are not well understood, limiting its precise management in the era of antibody‒drug conjugates. To address this issue, we established a cohort of 434 Chinese patients with HER2-low breast cancer (433 female and one male) and integrated genomic, transcriptomic, proteomic, and metabolomic profiling data. In this cohort, HER2-low tumors are more distinguished from HER2-0 tumors in the hormone receptor–negative subgroup. Within HER2-low tumors, significant interpatient heterogeneity also exists in the hormone receptor–negative subgroup: basal-like tumors resemble HER2-0 disease, and non-basal-like HER2-low tumors mimic HER2-positive disease. These non-basal-like HER2-low tumors are enriched in the HER2-enriched subtype and the luminal androgen receptor subtype and feature PIK3CA mutation, FGFR4/PTK6/ERBB4 overexpression and lipid metabolism activation. Among hormone receptor–positive tumors, HER2-low tumors show less loss/deletion in 17q peaks than HER2-0 tumors. In this work, we reveal the heterogeneity of HER2-low breast cancers and emphasize the need for more precise stratification regarding hormone receptor status and molecular subtype.

Performance of pre- and post-pembrolizumab vesical imaging–reporting and data system (VI-RADS) to predict the pathological response and efficacy outcomes in muscle-invasive urothelial bladder cancer (MIBC): Full data analysis from the PURE-01 trial.

65 Background: The VI-RADS is a standardized reporting system that uses multiparametric magnetic resonance imaging (mpMRI) parameters to differentiate non muscle-invasive bladder cancer (NMIBC) from MIBC. Limited data on clinical response assessment to neoadjuvant therapy are currently available. In this study, we aimed to analyze the performance of VI-RADS to predict the pT0 or pT≤1 response post-neoadjuvant immunotherapy in MIBC. Methods: In PURE-01 study (NCT02736266) patients (pts) were staged with mpMRI before and after treatment (3 cycles of Pembrolizumab) prior to radical cystectomy (RC). Logistic regression models analyzed pre- and post-pembro VI-RADS, with clinical and tumor-related variables, against ypT≤1N0 (primary endpoint) and ypT0N0 (secondary endpoint). VI-RADS scores were dichotomized between 0-3 (0 = no evidence of disease) and 4-5 (5 = extension to extravescical fat). Event-free survival (EFS) and overall survival (OS) analyses based on VI-RADS were performed. Comprehensive genomic profiling and transcriptome-wide expression profiling data were matched with VI-RADS scores. Model performance was also tested in the ongoing NureCombo (nivolumab+nab-paclitaxel; NCT04876313) and SURE-01 (sacituzumab govitecan; NCT05226117) neoadjuvant studies. Results: In total, 110 patients treated with neoadjuvant pembrolizumab between 02/2017 and 07/2020 had centrally reviewed scans (N=220 mpMRI). Pre-pembrolizumab, 21 patients (19.1%) had no measurable disease (VI-RADS=0), 34 (30.9%) had a VI-RADS 1-3 score, and 55 (50%) had a VI-RADS 4-5 score. Both pre-pembrolizumab and post-pembrolizumab VI-RADS 0-3 scores were the only significant covariates that predicted the ypT≤1N0 endpoint on multivariable analyses (MVA): the strongest effect was seen with post-pembrolizumab VI-RADS 0-3 predicting the ypT≤1N0 response (odds ratio [OR]: 23.4, 95%CI: 7-95.3, p&lt;0.0001). The area-under-the-curve (AUC) of this model was 0.90. Post-pembrolizumab VI-RADS 0-3 also predicted longer EFS (p&lt;0.001) and OS (p=0.044). The scores of several gene signatures from baseline tumors differed between pre-pembrolizumab VI-RADS 0-3 and 4-5 categories. RAF1 mutations were enriched in pre-pembrolizumab VI-RADS 0-3 group (p=0.045). Conclusions: VI-RADS scores post-pembrolizumab revealed a robust association with pathological downstaging and survival. VI-RADS scores were also characterized by distinct biomarker features. These results indicate that VI-RADS is emerging as an important tool to design next-generation trials in MIBC. Clinical trial information: NCT02736266 .