Translational Oncology

Objective Based on the bioinformatics method of multi-database integration, this study systematically analyzes the expression characteristics, clinical pathological correlation, prognostic value, potential molecular mechanisms, and immune infiltration patterns of hepatocyte growth factor receptor (MET) in gastric cancer. Methods The UALCAN and GEPIA databases were employed to examine the differential expression of MET between gastric cancer and normal gastric mucosal tissues, as well as its associations with clinicopathological features. Kaplan-Meier Plotter was utilized to evaluate the impact of MET expression on overall survival (OS) and progression-free survival (PFS). Protein-protein interaction (PPI) network was constructed via LinkedOmics, followed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of co-expressed genes. Four algorithms, TIMER, CIBERSORT, EPIC, and MCPcounter, were used to cross evaluate the correlation between MET expression and immune cell infiltration; Further validate the cell type specific expression of MET using the gastric cancer single-cell sequencing queues (GSE134520, GSE167297) built into the TISCH database. Results MET expression was significantly elevated in gastric cancer tissues compared with normal gastric mucosa (P < .05), and its expression level was significantly correlated with tumor grade and TNM stage. Patients with high MET expression exhibited significantly poorer OS and PFS than those with low MET expression (P < .05). The PPI network revealed that MET could interact with 20 key proteins, including EGFR, ERBB2, HGF, STAT3, and GRB2 etc. GO enrichment analysis suggests that differentially expressed genes are significantly enriched in functions such as the ERBB signaling pathway, cadherin binding, and DNA repair complexes; KEGG enrichment analysis showed that MET related genes were significantly enriched in pathways such as homologous recombination, nuclear cytoplasmic transport, mismatch repair, and oxidative phosphorylation. Immune infiltration analysis showed that the negative association between MET and B cells infiltration has cross algorithm robustness, while the association with neutrophils, CD8+ T cells, CD4+ T cells, and macrophages exhibits algorithmic heterogeneity or insignificance; There is no significant correlation between MET and common immune checkpoint molecules such as PD-1, PD-L1, CTLA4, etc. Single cell validation further confirmed that MET is mainly enriched in malignant epithelial cells and endothelial cells, and is almost not expressed in immune cells. Conclusions Multidimensional bioinformatic analyses demonstrate that elevated MET expression serves as an independent risk factor for unfavorable prognosis in gastric cancer. MET may mediate dual drug resistance in gastric cancer via crosstalk with multiple signaling molecules (including EGFR, ERBB2, HGF, STAT3 and GRB2) and dysregulation of the homologous recombination repair pathway. Results from multiple-algorithm immune infiltration analysis, single-cell dataset analysis and immune checkpoint correlation analysis indicate that MET exerts only modest direct regulatory effects on the gastric cancer immune microenvironment. This exploratory study offers systematic bioinformatic evidence supporting MET as a candidate prognostic biomarker and potential therapeutic target for gastric cancer. Further functional experiments and prospective cohort studies are required to validate its molecular mechanisms and clinical utility.

Purpose Tarlatamab, a bispecific T-cell engager, has generated favorable response and survival outcomes in relapsed small cell lung cancer (SCLC). Factors influencing tarlatamab-associated treatment outcomes and toxicity have yet to be established. We performed a multivariate analysis to identify biomarkers associated with cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS) and integrated these variables into a novel risk stratification tool to identify patients at high risk of clinically significant toxicity. Patients and Methods Logistic and ordinal regression analyses evaluated the predictive value of variables contributing to the presence and severity, respectively, of CRS and ICANS in 115 patients with ES-SCLC receiving tarlatamab. Selected variables were then tuned using 5-fold cross-validation and incorporated into novel elastic net-based prediction models. Results Rates of observed CRS, ICANS, and dysgeusia were 46%, 28%, and 47%, respectively. ORR (overall response rate) and DCR (disease control rate) were 44% and 58.2%, while 6-month PFS (progression free survival) and OS (overall survival) rates were 30.4% and 54.9%, respectively. Excluding patients on tarlatamab <30 days, presence of dysgeusia was associated with a lower rate of disease progression (HR 0.44, p=0.00691) and death (HR 0.34, p=0.0145). The presence of, increased size and number of extracranial metastases as well as elevated baseline LDH were significantly associated with increased likelihood of CRS. Increased ECOG performance status, increased volume of brain metastases, development of CRS, and elevated baseline LDH were all associated with increased risk of developing ICANS. Our cross-validated risk model successfully predicted CRS grade [&ge;]2 and ICANS events with 90.9% and 75% sensitivity, respectively. Conclusions This exploratory analysis identified several predictive biomarkers of toxicity that successfully stratified low and high-risk populations as part of an internally validated novel risk scoring tool.

Circulating tumor cells (CTCs) are key drivers of distant metastasis, while platelets facilitate this process by protecting them from immune surveillance. However, the detection of CTCs exhibiting platelet markers and their communication with monocytes has not been thoroughly investigated. This study seeks to identify the intercellular communication of CTCs that have acquired platelet traits by integrating single-cell RNA-seq data of 377 CTCs and 2,634 white blood cells. Trajectory analysis identified a subpopulation of CTCs with enhanced platelet-related functions, including platelet aggregation and resistance to NK cell-mediated cytotoxicity, termed Platelet-Programmed CTCs. The Dampened Weighted Least Squares method was implemented to estimate the platelet-programmed tumor cell proportion in 1,102 bulk RNA-seq samples from primary breast cancer tumors. A strong inverse association was found between platelet-programmed tumor cell proportion and overall survival (Cox-PH p-value =0.00419, HR=6 per 10% increase in proportion, 95% CI:1.76-20.7). However, this association did not differ significantly between early- and late-stage patients. Cell-cell communication analyses and molecular docking revealed the CD40LG-ITGA5:ITGB1 pair as a potential immune checkpoint candidate for monocytes in cancer (Hex score=-656.83; TNF-TNFR reference complex=-515). However, further experimental and clinical validation is required to translate these findings. In conclusion, these findings deepen our understanding of the immune evasion mechanisms of CTCs by acquiring platelet characteristics. This immune checkpoint axis offers a novel avenue for further experimental validation and future intervention.

Triple-negative breast cancer (TNBC) is a highly aggressive malignancy and options for targeted therapy are limited. Although PARP inhibitors (PARPi) like olaparib (Ola) leverage synthetic lethality, their clinical utility is severely impeded by drug resistance and low frequency of BRCA mutations. In this study, 1,2,3,4,6-penta-O-galloyl-{beta}-D-glucose (PGG), a natural polyphenolic compound, can induce a state of homologous recombination deficiency (HRD) in TNBC cells by inhibiting the PALB2-BRCA2 interaction. PGG potentiated the inhibitory effects of Ola on the in vitro proliferation, clonogenic potential, migration, and invasion of TNBC cells. Mechanistically, the dual therapy triggered severe oxidative stress and mitochondrial collapse, which accelerated the classical apoptosis cascade and promoted the emission of immunogenic cell death (ICD)-associated DAMPs. The accumulated cytosolic double-stranded DNA activated the innate immune cGAS-STING pathway, thereby promoting robust intra-tumoral infiltration of CD8+ T cells. Furthermore, since cGAS-STING hyperactivation drives compensatory PD-L1 upregulation on TNBC cells, incorporating anti-PD-L1 antibody into the combination regimen further reversed the immunosuppressive barrier, achieving near-complete tumor eradication and maximum infiltration of cytotoxic T cells in vivo. Bioinformatics analyses further suggested a potential network of PGG targets associated with extracellular matrix organization, offering a bioinformatics-derived hypothesis for its theoretical involvement in modulating stromal tension and vascular homeostasis. Collectively, this study establishes PGG as a multi-functional therapeutic agent integrating intracellular synthetic lethality and innate immune sensing, while providing a preliminary bioinformatic rationale for prospective microenvironmental investigation. This study also shows PGG as a multi-functional therapeutic agent that integrates intracellular synthetic lethality, innate immune sensing, and microenvironmental remodeling to convert immunologically "cold" TNBC into "hot" tumors.

Pancreatic ductal adenocarcinoma (PDAC) arises within an extensively remodeled microenvironment, yet tissue markers that distinguish invasive carcinoma from precursor lesions remain limited. Integrating four single cell RNA sequencing atlases comprising 324,662 cells from 26 patients, we identified cancer associated fibroblast expansion, accumulation of C1QA+ immunoregulatory macrophages, and depletion of a dendritic cell compartment expressing plasmacytoid markers. Fibroblasts were enriched for extracellular matrix and PI3K AKT programs and macrophages for an antigen-presentation program. We then examined the protein level correlates of these populations in a tissue proteomic reference framework of 356 samples spanning non diseased pancreas, normal-adjacent tissue, low and high grade intraductal papillary mucinous neoplasms (IPMNs), IPMN associated invasive carcinoma, and PDAC, prioritizing proteins that changed monotonically across the six histopathologic reference groups or marked tumor enriched cell types. Despite depletion of plasmacytoid dendritic cells, the principal source of type I interferon, the interferon stimulated protein ISG15, expressed by both fibroblasts and macrophages, increased monotonically toward PDAC. In exploratory cross-validated benchmarking of PDAC versus low and high grade IPMN, excluding IPMN-associated invasive carcinoma (145 versus 56 samples), CATB+EPIPL achieved an AUC of 0.98, with a sensitivity of 92% at an achieved specificity of 92%, exceeding protein abundance models of diagnostic IHC-associated markers (S100P+IMP3+maspin+MSLN, 0.79) and refitted published IPMN progression combinations (<0.91). Against non diseased pancreas, candidate and comparator panels performed similarly (AUC 0.99 1.00). These biologically informed tissue protein panels warrant independent validation, including immunohistochemical evaluation of EUS guided fine needle biopsy specimens and measurement in blood.

Poly (ADP-ribose) polymerase inhibitors (PARPi) are the only targeted treatment available for early triple-negative breast cancer (TNBC), an aggressive subtype with limited treatment options. While PARPi are effective in patients with BRCA mutations, resistance to these inhibitors can arise. We previously developed BRCA-mutant cell lines, HCC1395, with acquired resistance to talazoparib and olaparib, and have now developed PARPi-resistant MX1 cell lines in an analogous manner. Ribosomal pathways were upregulated in 3/4 cell lines with acquired PARPi resistance. The resistant cell lines showed high and low basal nucleolar stress based on nucleolar morphology and nucleophosmin delocalization from nucleolus to nucleoplasm. Treatment of these cell lines with the combination of olaparib and a ribosome biogenesis inhibitor, BMH-21, demonstrated synergy in the PARPi-resistant cell lines, but not in the parental cells. Interestingly, HCC1395 cells, which had lower baseline nucleolar stress, showed greater nucleophosmin delocalization with combination treatment than MX1 cells, which had higher baseline nucleolar stress. All four cell lines demonstrated sustained DNA damage with the combination. We extended our investigation to 3 BRCA wild-type TNBC cell lines, BT549, Hs578T, and MDAMB231 and identified synergy in the context of intrinsic PARPi resistance. In MDAMB231 cells, combining olaparib with BMH-21 induced a senescence-like phenotype, increasing gH2AX-positive cells by up to 7.3-fold, senescence-associated B-galactosidase (SA-B-gal) staining by 5.6-fold, and p21 by 3.6-fold. These results were mirrored with a second ribosome biogenesis inhibitor, CX-5461. Finally, we identified distinct patterns of ribosomal pathway activity in a cohort of patients with treatment-resistant TNBC, and found correlations between ribosomal pathways with MYC, proliferation, DNA damage, and senescence. Together, these data identify ribosome biogenesis as a potential therapeutic vulnerability in PARPi-resistant TNBC and support its targeting in combination with PARPi, while demonstrating a broader for ribosome biogenesis in treatment-resistant TNBC.

Background: Human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) shows higher prevalence of lymph node metastases than HPV-negative OPSCC. It remains unclear whether HPV-positive and HPV-negative OPSCC differ in occult metastasis risk, which is relevant to personalize elective nodal treatment volumes. Methods: We performed a retrospective analysis of 780 untreated OPSCC patients from four European centers. Patterns of lymph node level involvement (LNLs I, II, III, IV, V, VII) were assessed using a consensus diagnosis integrating imaging (CT, MRI, PET) and pathological findings from surgically treated patients. Occult metastases were assessed in 288 surgical patients with paired clinical and pathological information. Results: HPV-positive patients more frequently presented with ipsilateral LNL II involvement, particularly in early T-stage disease (80.6% [75.6-84.8] vs. 54.8% [47.2-62.2]). However, the probability of downstream involvement in LNLs III and IV conditioned on upstream LNL involvement was similar between HPV-positive and HPV-negative patients. Similarly, contralateral involvement conditioned on midline extension of the primary tumor was similar. The overall proportion of occult metastases, defined as clinically false-negative LNLs divided by pathologically positive LNLs, was lower in HPV-positive patients (24.7% [19.7-30.1] vs. 48.7% [39.7-57.8]). Conclusions: HPV-positive OPSCC showed higher prevalence of LNL involvement, especially in ipsilateral LNL II and early T-stage tumors. The data to directly compare occult metastasis risk has important limitations and does not allow definitive conclusions. However, the presented data suggests that higher prevalence likely does not translate into higher risk of occult metastases for the most common clinical diagnoses and therefore does not support larger elective nodal treatment volumes compared with HPV-negative tumors.

Introduction: Tumors are known to develop genomic heterogeneity over time, particularly in metastatic disease, raising concerns that a single-site biopsy may be insufficient to accurately predict response to medications. Methods: We used our 3D microtumor functional profiling platform that preserves key features of the native tumor microenvironment. We tested (i) six split samples from primary tumors and (ii) seven samples from primary tumors (ovarian, colon, and breast cancer) matched with their locoregional or distant metastases. Fresh tissue specimens were processed within 24 hours after surgery and treated with NCCN guideline-recommended chemo or targeted therapies at concentrations over four orders of magnitude. Cytotoxicity was evaluated after three days to generate dose response curves. The response correlations between the split sample or between the two matched sites were quantified using the concordance correlation coefficient ({rho}c) for the drug efficacy metrics. Results: We compared a total of 275 drug responses. The six split samples resulted in a strong correlation between the two tumor areas ({rho}c=0.95, p<0.001), supporting high assay reproducibility across distinct regions of the same tumor. Locoregional metastases were highly correlated with their primaries (ovarian to omentum {rho}c=0.97, p<0.001; ovarian to liver capsule {rho}c=0.93, p<0.001; colon to peritoneum {rho}c=0.91, p<0.001). A lesser correlation was observed with lymphogenic metastases (breast to axilla {rho}c=0.87, p<0.001), and the correlations of hematogenic metastases were even lower (colon to lung {rho}c=0.69 p<0.001; ovarian to soft tissue/colon {rho}c=0.58, p<0.001). No correlation was observed among specimens that were resistant to all tested medications. Conclusion: Tumor drug responses were highly preserved in locoregional metastases, whereas somewhat greater divergence was observed in lymphogenic or hematogenic metastases. Single-site functional profiling may remain informative for identifying treatment resistance and might reduce the risk of ineffective therapy selection in metastatic disease.

Cisplatin remains as standard chemotherapy for patients with HNSCC, but rapid development of drug resistance has limited patient benefit. The p53 tumor suppressor plays a central role in the cellular response to DNA damage in cancer, triggering apoptosis to prevent propagation of damaged cells in tumor development. TP53 gene mutations occur in 65-86% of HNSCC. Small molecule PG3 induces the integrated stress response (ISR), leading to apoptosis via the HRI-eIF2-ATF4-PUMA axis. We hypothesized that a combination of PG3 plus cisplatin could increase apoptosis in TP53-mutated HNSCC cells through enhanced induction of the ISR and ATF4. PG3 synergized with cisplatin to inhibit cell viability, leading to potent apoptosis in TP53-deficient cells. The effect was regulated through the HRI-ATF4-NOXA pathway. Furthermore, we identified that cisplatin activates HRI and leads to the degradation of CReP (constitutive repressor of eIF2 phosphorylation) via E3 ligase {beta}-TrCP, contributing to the induction of the ISR. We noted decreased ATF4 levels after treatment with cisplatin, CPT, or PG3 and cisplatin. Thus, combined therapy of PG3 plus cisplatin likely results in adaptation and acquired resistance via degradation of ATF4. We targeted the degradation mechanism of ATF4 by inhibiting {beta}-TrCP1, CK1{delta}, or CK2, respectively. Each approach successfully blocked ATF4 degradation induced by cisplatin or PG3 plus cisplatin and enhanced apoptosis. Our results provide a rational strategy for triple treatments, involving an ISR inducer, a DNA damaging drug, and a {beta}-TrCP inhibitor/CK1{delta} inhibitor/CK2 inhibitor, to achieve potent and prolonged anti-tumor effects and overcome chemoresistance in HNSCC.

The immunomodulatory effects of chemotherapy (chemoimmunomodulation; CIM) are clinically consequential and heterogeneous, yet no systematic framework exists for classifying the immunomodulatory trajectory a tumor follows in response to treatment (CIM trajectory). Here, we present the CIM Induction Classifier (CIMIC), an unsupervised clustering pipeline leveraging delta gene expression across 3,189 CIM-related genes to classify specimens chemoimmunomodulatory trajectory. Applied to two pre- and post-chemotherapy breast cancer (BC) datasets (NKI/SMC, N = 36; NEO, N = 19) and nine epirubicin-perturbed triple-negative BC (TNBC) cell lines, CIMIC identified two divergent CIM trajectories: a functional CIM (Fun-CIM) trajectory, broadly conserved across tumors and cell lines and characterized by induction of inflammatory cell death, antigen presentation, viral mimicry, and adaptive immune activation programs, and a dysfunctional CIM (Dys-CIM) trajectory, characterized by induction of proteostatic and metabolic stress-adaptation programs, reduced immune cell abundances and cytotoxic activity, and enrichment of aggressive BC subtypes. Using survival and longitudinal transcriptomic data in NKI/SMC (N = 20), treatment-induced increases in Fun-CIM-associated genes and ssGSEA scores were associated with reduced recurrence, whereas Dys-CIM-associated genes and scores were associated with increased recurrence. In multivariable analyses within independent chemotherapy-treated BC cohorts (METABRIC, N = 412; SCAN-B, N = 2,462), higher baseline Fun-CIM ssGSEA scores were associated with better outcomes, whereas higher baseline Dys-CIM ssGSEA scores were associated with worse outcomes. These findings establish CIM as a dynamic, trajectory-level process and position CIMIC as a framework for defining CIM trajectories and supporting future efforts to identify predictors, mechanisms, and therapeutic strategies that maximize beneficial CIM.

PURPOSEPancreatic ductal adenocarcinoma (PDAC) is a deadly malignancy with poor prognosis. A transcriptomic-based algorithm called Purity Independent Subtyping of Tumors (PurIST) relies on expression profiling of a defined set of genes to stratify PDAC into classical and basal-like molecular subtypes and assigns a confidence level to the subtypes as either "strong," "likely," or "lean." In this study, we apply PurIST to Appalachian and non-Appalachian patient cohorts and assess demographic variables between groups that may influence treatment outcomes. PATIENTS AND METHODSThis 13-site study includes 780 PDAC patients. Patients were divided into Appalachian and non-Appalachian cohorts according to Appalachian Regional Commission guidelines, and differences in PurIST classification, tobacco use, and alcohol use were analyzed. RESULTSIndividuals from Appalachian regions were more likely to receive a subtype classification from PurIST with "strong" confidence as opposed to "likely" or "lean" (P=0.0175; odds ratio=1.66). We did not observe any significant difference between basal and classical subtype classification in Appalachia (P=0.1457), yet an exploratory analysis showed that individuals aged [&ge;]85 were significantly more likely to have basal-like tumor classifications (P=0.005817; odds ratio=3.79). Appalachian patients were more likely to have a history of smoking (59.6% vs 49.9%; P=0.01756) and less likely to report alcohol consumption (50.5% vs 65.6%; P=0.000229). CONCLUSIONWe conducted the largest comparison of the PurIST algorithm in Appalachia to date and found PurIST is more likely to have higher confidence in molecular subtype classifications for Appalachian PDAC tumors compared to non-Appalachian tumors. If PurIST is to be considered as a prognostic or decision-making tool for PDAC patients, we must account for variability in different populations and model the likelihood that tumors will have a strong molecular signature.

Ovarian cancer stands out as one of the most lethal gynecological cancers among women in the United States. While patients with ovarian cancer often show positive responses to treatment, it is common for the cancer to reappear and develop resistance to treatment, so it is important to explore and create novel combinations to increase patient survival rates. ATRi (Ataxia telangiectasia and Rad3-related inhibitors) and ONC201 monotherapies have shown efficacy in ovarian cancer in preclinical models. We hypothesized that combining ATRi with ONC201 would enhance this efficacy. ONC201 induces apoptosis through the TRAIL-pathway following activation of the integrated stress response and inactivation of Akt which is upregulated in ovarian cancer. Six human ovarian cancer cell lines were treated alone and with the novel drug combination of ceralasertib (ATRi) and ONC201. We found an IC50 range of 0.88-20.16 microM for ONC201 and IC50 range of 0.55-54.75 microM for ceralasertib. The combination of ONC201 plus ceralasertib resulted in PARP cleavage consistent with apoptosis along with reduction in Bcl-XL, Xiap and p-Akt expression after 72 hours of treatment. Cytokine profiling showed a decrease in markers of inflammation and tumor progression. Our data provide evidence of synergy from the combination of ATRi ceralasertib and ONC201 against Ovarian cancer cells that merits further investigation including clinical translation.

Background & AimsWe previously developed multiple machine-learning and regression-based risk prediction models using retrospective electronic health records (EHR) to estimate near-term risk of pancreatic cancer (PC). This pilot study aimed to assess the feasibility of an early detection strategy combining initial EHR-based risk prediction with downstream imaging and blood-based testing. MethodsThis prospective study included adults aged 50-84 years with an estimated [&ge;]1% 18-month risk of PC, identified between January 2021 and March 2023 using four previously validated models. Patients with a history or active suspicion of PC were excluded. Participants completed cross-sectional imaging and CA19-9 labs at baseline and again at 18 months. Outcomes included enrollment rates, test completion rate, and burden of incidental findings. ResultsOf 1,251 eligible patients, 102 (8.2%) enrolled (median age 69 years [IQR 62-75]; 58% women; 48% Hispanic, 34% White, 11% Black, and 7% Asian). At baseline, 89 (87%) completed imaging and 98 (96%) completed CA19-9. At 18 months, 79% completed both imaging and CA19-9. Ten (10%) participants underwent additional clinical evaluations triggered by imaging findings. Evaluations included an endoscopic ultrasound, renal imaging, and FibroScan. CA19-9 results were normal in most participants, though 18% had elevated levels at baseline. ConclusionsReal-time EHR-based ML algorithms can be combined with blood- and imaging-based surveillance for early detection of PC with acceptable burden of incidental findings. However, improved patient engagement is a key aspect that will need to be addressed in order to successfully scale an AI-guided strategy for early detection.

Background/Objectives: In high-grade serous ovarian cancer (HGSOC), the abilities of tumor cells to resist cytotoxic treatment and relapse are largely driven by ovarian cancer stem cells (CSCs). CSCs are a population of cells within a tumor that maintain stem-like qualities and have the capacity to produce metastasis and drive drug resistance. Based on the complexity of CSC signaling and emerging evidence of differential isoform usage in development, we hypothesize that CSCs possess a patient-specific, heterogeneous landscape which exploits isoform diversity to sustain stemness, metastasis and drug resistance. Methods: RNA-seq was generated from 3 patient-derived HGSOC (PD-HGSOC) to investigate stemness and differentiation status comparing standard culture and CSCs. The data was analyzed at both gene- and isoform-levels to identify patient-specific CSC features and define mechanisms of cancer-related stemness and plasticity. Results: CSCs exhibited higher stemness characteristics and identified differentially expressed gene sets across PD-HGSOCs. We noted that each patient had a distinct subset of genes regulating stemness phenotypes which suggested multiple mechanisms of CSC development and maintenance. Additionally, a large proportion of gene-level expression changes were driven by the differential expression of a single predominant isoform. Importantly, our isoform-level analysis enabled the identification of differential isoform usage that would not be detected with gene level expression analysis. Conclusions: CSC phenotypes such as chemoresistance, metastasis and self-renewal are conserved across patients, but arise from largely patient-specific gene and isoform programs. This CSC heterogeneity is reflective of the heterogeneity seen in patients and should be further evaluated in deriving precision-medicine approaches for HGSOC.

ABSTRACT BACKGROUND: Next-generation sequencing (NGS) and the development of targeted therapies have revolutionized cancer treatment. Molecular Tumour Boards (MTB) serve as collaborative platforms to integrate individual clinical and molecular information to make recommendations for personalized treatment. METHOD: This is a single-center, retrospective cohort study of patients presented at the Jewish General Hospital (JGH) MTB between July 2018 and Dec 2022. Clinical, molecular/pathologic data, MTB recommendations, and treatment details were collected. Treatment response was determined by radiological evaluation and physician clinical assessment. Fishers exact test and Log-rank tests were used to assess differences between groups. RESULTS: A total of 328 patients were presented to the MTB, including 23 with repeat presentations, resulting in 355 case reviews. Tumour-agnostic biomarkers were detected in 18.9% of cases, most commonly high tumour mutational burden (TMB, 9.5%) and HER2 amplification (4.3%). The most frequent actionable mutations were PIK3CA (19.8%) and PTEN (13.1%), often leading to recommendations for mTOR inhibitor therapy (26.0%). Overall, therapeutic recommendations were issued in 84.5% (300/355) of cases, and implemented in 43.3% (130/300). Patients who received MTB-recommended therapies achieved significantly higher objective response rates (ORR) (14.2% vs. 4.2%; P = 0.047), longer real-world progression-free survival (rwPFS) (5.6 vs. 3.5 months; HR 0.57; 95% CI 0.390 - 0.828; P = 0.003), and improved median overall survival (OS) (12.8 vs. 5.2 months; HR 0.60, 95% CI 0.452 - 0.793; P < 0.001) compared with those treated without MTB guidance. CONCLUSION: MTB is effective in identifying biomarker-matched therapeutic recommendations for advanced malignancies where limited standard-of-care treatment option is available.

Purpose: Cyclin-dependent kinase 4/6 inhibitors in combination with endocrine therapy have become widely adopted as a first-line treatment approach for hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC). Through a collaboration between Novartis and the US Food and Drug Administration, we integrated multimodal data from phase III MONALEESA trials to identify novel prognostic factors for HR+/HER2- ABC. Experimental Design: Baseline clinical and genomics data were collected from patients in the MONALEESA-2, -3, and -7 trials. Circulating tumor DNA (ctDNA) from plasma samples and gene expression in archival tumor biopsies were analyzed. Machine learning models were trained (n = 1,355) on progression-free survival (PFS) using multimodal features via fusion models. In a test set (n = 382), prognostic performances were evaluated using the Kaplan-Meier, Cox, and Weibull models. Results: The late fusion model achieved a prognostic performance (C-index: 0.727, 95% CI: 0.641-0.799) slightly outperforming early fusion (C-index: 0.718, 95% CI: 0.631-0.791) and single-modality models. Model-based risk stratification identified distinct low- and high-risk groups (PFS HR, 0.28; 95% CI: 0.20-0.38). Among the top 40 features for progression risk (18 clinical, 20 gene expression, and 2 ctDNA), these were associated with higher risk: liver involvement, higher histological grades, early relapse; lower STC2 and RBBP8 expressions and higher FBX05 expression; and higher tumor mutational burden and ctDNA purity. Conclusions: Integrating clinical and genomic modalities improved progression risk prediction compared with single-modality models, while highlighting salient features that inform the underlying biology and support hypothesis generation.

The FORESEE trial (NCT04450706) was a prospective study to evaluate the feasibility of integrating organoid-based drug testing with comprehensive genomic characterization to inform treatment selection in patients with HER2-negative metastatic breast cancer. The primary objective of the study was to determine the feasibility of providing personalized therapy recommendations using a combination of genomic vulnerability information with drug testing in patient-derived organoids (PDOs) in a clinically relevant time frame. Of the 15 patients enrolled, 10 cases had biopsies with adequate tumor content, and PDOs were successfully established in 4 of 10 cases. Drug profiling and genomic testing was completed in all established organoids, yielding an overall success rate of 40% in cases of biopsies with adequate tumor content. Drug sensitivity and genomic results were returned within 12 weeks and informed subsequent treatment selection in all evaluable cases. The primary endpoint - demonstrating that PDO-based drug screening combined with genomic characterization would identify clinically actionable outcomes in at least 46% of patients based on prior data - was not met. In conclusion, successful PDO establishment represents a limiting step in the implementation of FPO for metastatic breast cancer; however when PDO were successful, drug responses were always obtained and physicians chose to use the information in 100% of cases. These findings highlight the need for improved strategies optimizing use of patient biopsy material for drug testing in order to fully realize the clinical potential of FPO.

Purpose: Uveal melanoma (UM) is a rare but aggressive intraocular malignancy originating in the uvea (choroid, iris, and ciliary body). Despite primary treatment, 50% of UM patients develop metastases to the liver, lungs, bones, and skin. Topotecan, a topoisomerase I inhibitor, and SP141, an MDM2 inhibitor, have been studied in cancers, including retinoblastoma. This study explores a combined approach with these drugs in the 92-1 UM cell line. Methods: Primary choroidal melanoma-derived 92-1 cells were treated with topotecan and SP141 individually to determine IC50 values. Cell viability and proliferation were assessed using the MTT assay and the xCELLigence real-time monitoring system. The synergistic effects were analyzed quantitatively using the Loewe Additivity and Highest Single-Agent (HSA) models. Flow cytometry was employed to analyze cell cycle distribution, while cell death and apoptosis were monitored via high-throughput, real-time quantitative analysis using the IncuCyte live-cell kinetic imaging system. Results: Both Topotecan and SP141 induced significant cell death in 92-1 cells. xCELLigence showed dose- and time-dependent inhibition of proliferation. Combining sub-IC50 concentrations of topotecan and SP141 exhibited significant synergistic effects, markedly reducing growth. Cell cycle analysis revealed that topotecan causes a dose-dependent biphasic arrest in G2 and S phases, while SP141 causes G2/M arrest, leading to cell death. Cytotoxicity assays corroborated increased cell death following combination therapy, and the Caspase 3/7 assay indicated that apoptosis is the mechanism underlying cell death. Conclusions: The multi-targeted approach combining topotecan and SP141 drugs demonstrated synergistic therapeutic effects in 92-1 cells, suggesting a potential treatment strategy for managing UM.

Background Chemotherapy (CT) de-escalation strategies based on dual HER2 blockade with trastuzumab and pertuzumab (HP) have shown promising efficacy in HER2-positive (HER2+) early breast cancer (EBC), but biomarkers to guide patient selection are lacking. The Ataraxis Breast platform (ATX) uses artificial intelligence (AI) models integrating hematoxylin-eosin (H&E) whole-slide images and clinical variables to predict pathological complete response (pCR) and long-term outcomes. We evaluated ATX in the phase II PHERGain (NCT03161353) and PHERGain-2 (NCT04733118) trials. Methods The ATX NEO model was assessed for pCR prediction in PHERGain (n=306 evaluable patients) and PHERGain-2 (n=383 evaluable patients). The ATX RISK model was evaluated for prognosis in PHERGain (n=309 evaluable patients). Prespecified cutoffs classified patients into low-, medium-, and high-probability groups for pCR and low- or high-risk groups for recurrence. Associations with pCR were assessed using logistic regression. Prognostic performance was evaluated using Cox proportional hazards models, Kaplan-Meier estimates, and Harrell's C-index. Results Overall pCR rates were 40.2% in PHERGain and 60.3% in PHERGain-2. Continuous NEO scores were significantly associated with pCR in both PHERGain (odds ratio [OR], 1.28; 95% CI, 1.11-1.48; P<0.001) and PHERGain-2 (OR, 1.30; 95% CI, 1.13-1.52; P<0.001). Using prespecified cutoffs, pCR rates increased across low-, medium-, and high-probability groups (19.2%, 41.3%, and 48.3% in PHERGain; 29.5%, 61.6%, and 70.1% in PHERGain-2). In PHERGain, the RISK score was significantly associated with event-free survival (hazard ratio per 1-SD increase, 1.56; 95% CI, 1.17-2.08; P=0.002; C-index, 0.66). Five-year event-free survival was 93.9% in the low-risk group and 83.1% in the high-risk group. Conclusions NEO score was consistently associated with pCR across two independent HER2+ EBC trials, while RISK score provided prognostic information for long-term outcomes in PHERGain. Prespecified score categories identified clinically distinct response and risk groups. These findings support further evaluation of AI-based biomarkers to refine patient selection for CT de-escalation strategies in HER2+ EBC.

Prostate cancer (PCa) is the most commonly diagnosed cancer and the second leading cause of cancer death among US men. Metastatic castration-resistant PCa (mCRPC) is a clinically advanced form of PCa, often associated with increased aggressiveness, metastatic potential, morbidity, and a higher risk of developing resistance to taxanes (TX), the first-line chemotherapy for mCRPC. Furthermore, cancer stemness and epithelial to mesenchymal trans-differentiation (EMT) potentially contribute to aggressiveness and the development of drug resistance in mCRPC. Here, we applied our drug development pipeline, secDrug, which utilizes a pharmacogenomics data-driven computational algorithm, to demonstrate that TAK-715 - a dual inhibitor of p38 MAPK and Casein kinase {delta}/{epsilon}, is a promising treatment for these advanced/lethal variants of PCa. Using in vitro cytotoxicity assays followed by cell-based functional assays in a panel of mCRPC cell lines representing TX-sensitive mCRPC, clonally derived TX-resistant lines, and a highly aggressive metastatic variant of mCRPC, we demonstrated the efficacy of TAK-715 treatment as a single agent and in combination with TX, including cancer stem-like cells. Further, we showed that the apoptotic effects of TAK-715 occur via a mitochondrial-mediated pathway. Bulk tumor RNA sequencing followed by pathway analysis identified genes associated with mitochondrial dysfunction and cell cycle arrest as the top molecular networks associated with TAK-715 single-treatment. HES1, a gene associated with nodal metastasis and PCa progression, was the top differentially expressed gene. Single-cell transcriptomics analysis revealed that TAK-715 treatment erodes the subclonal populations responsible for cancer stemness, metastasis, and drug resistance. The clinical significance of these findings was validated in silico using multiple patient datasets. Our results suggest that TAK-715 treatment has the potential to decrease oncogenic progression and cancer stem cell-like activity in drug-resistant, aggressive, and stem-like mCRPC cells.