TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy.

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.

Mechanisms of resistance to oncogenic KRAS inhibition in pancreatic cancer.

KRAS inhibitors demonstrate clinical efficacy in pancreatic ductal adenocarcinoma (PDAC); however, resistance is common. Among patients with KRASG12C-mutant PDAC treated with adagrasib or sotorasib, mutations in PIK3CA and KRAS, and amplifications of KRASG12C, MYC, MET, EGFR, and CDK6 emerged at acquired resistance. In PDAC cell lines and organoid models treated with the KRASG12D inhibitor MRTX1133, epithelial-to-mesenchymal transition and PI3K-AKT-mTOR signaling associate with resistance to therapy. MRTX1133 treatment of the KrasLSL-G12D/+;Trp53LSL-R172H/+;p48-Cre (KPC) mouse model yielded deep tumor regressions, but drug resistance ultimately emerged, accompanied by amplifications of Kras, Yap1, Myc, and Cdk6/Abcb1a/b, and co-evolution of drug-resistant transcriptional programs. Moreover, in KPC and PDX models, mesenchymal and basal-like cell states displayed increased response to KRAS inhibition compared to the classical state. Combination treatment with KRASG12D inhibition and chemotherapy significantly improved tumor control in PDAC mouse models. Collectively, these data elucidate co-evolving resistance mechanisms to KRAS inhibition and support multiple combination therapy strategies.

New-onset diabetes is a predictive risk factor for pancreatic lesions in high-risk individuals: An observational cohort study.

Background and Objectives: Pancreatic cancer (PC) is the third cause of cancer-related deaths. Early detection and interception of premalignant pancreatic lesions represent a promising strategy to improve outcomes. We evaluated risk factors of focal pancreatic lesions (FPLs) in asymptomatic individuals at hereditary high risk for PC. Methods: This is an observational single-institution cohort study conducted over a period of 5 years. Surveillance was performed through imaging studies (EUS or magnetic resonance imaging/magnetic resonance cholangiopancreatography) and serum biomarkers. We collected demographic characteristics and used univariate and multivariate logistic regression models to evaluate associations between potential risk factors and odd ratios (ORs) for FPL development. Results: A total of 205 patients completed baseline screening. Patients were followed up to 53 months. We detected FPL in 37 patients (18%) at baseline; 2 patients had lesions progression during follow-up period, 1 of them to PC. Furthermore, 13 patients developed new FPLs during the follow-up period. Univariate and multivariate analyses revealed that new-onset diabetes (NOD) is strongly associated with the presence of FPL (OR, 10.94 [95% confidence interval, 3.01-51.79; P < 0.001]; OR, 9.98 [95% confidence interval, 2.15-46.33; P = 0.003]). Follow-up data analysis revealed that NOD is also predictive of lesions progression or development of new lesions during screening (26.7% vs. 2.6%; P = 0.005). Conclusions: In a PC high-risk cohort, NOD is significantly associated with presence of FPL at baseline and predictive of lesions progression or new lesions during surveillance.

TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer.

Resistance to immune checkpoint therapy (ICT) presents a growing clinical challenge. The tumor microenvironment (TME) and its components, namely tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs), play a pivotal role in ICT resistance; however, the underlying mechanisms remain under investigation. In this study, we identify expression of TNF-Stimulated Factor 6 (TSG-6) in ICT-resistant pancreatic tumors, compared to ICT-sensitive melanoma tumors, both in mouse and human. TSG-6 is expressed by CAFs within the TME, where suppressive macrophages expressing Arg1, Mafb, and Mrc1, along with TSG-6 ligand Cd44, predominate. Furthermore, TSG-6 expressing CAFs co-localize with the CD44 expressing macrophages in the TME. TSG-6 inhibition in combination with ICT improves therapy response and survival in pancreatic tumor-bearing mice by reducing macrophages expressing immunosuppressive phenotypes and increasing CD8 T cells. Overall, our findings propose TSG-6 as a therapeutic target to enhance ICT response in non-responsive tumors.

A Rigorous Multi-Laboratory Study of Known PDAC Biomarkers Identifies Increased Sensitivity and Specificity Over CA19-9 Alone.

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs. We analyzed the training set to identify candidate biomarker combination panels using biomarkers across laboratories, and we applied the fixed panels to the validation set. The panels identified in the training set, CA19-9 with CA199.STRA, LRG1, TIMP-1, TGM2, THSP2, ANG, and MUC16.STRA, achieved consistent performance in the validation set. The panel of CA19-9 with the glycan biomarker CA199.STRA improved sensitivity from 0.44 with 0.98 specificity for CA19-9 alone to 0.71 with 0.98 specificity (p < 0.001, 1000-fold bootstrap). Similarly, CA19-9 combined with the protein biomarker LRG1 and CA199.STRA improved specificity from 0.16 with 0.94 sensitivity for CA19-9 to 0.65 with 0.89 sensitivity (p < 0.001, 1000-fold bootstrap). We further validated significantly improved performance using biomarker panels that did not include CA19-9. This study establishes the effectiveness of a coordinated study of previously discovered biomarkers and identified panels of those biomarkers that significantly increased the sensitivity and specificity of early-stage PDAC detection in a rigorous validation trial.

Nardilysin-regulated scission mechanism activates polo-like kinase 3 to suppress the development of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) develops through step-wise genetic and molecular alterations including Kras mutation and inactivation of various apoptotic pathways. Here, we find that development of apoptotic resistance and metastasis of KrasG12D-driven PDAC in mice is accelerated by deleting Plk3, explaining the often-reduced Plk3 expression in human PDAC. Importantly, a 41-kDa Plk3 (p41Plk3) that contains the entire kinase domain at the N-terminus (1-353 aa) is activated by scission of the precursor p72Plk3 at Arg354 by metalloendopeptidase nardilysin (NRDC), and the resulting p32Plk3 C-terminal Polo-box domain (PBD) is removed by proteasome degradation, preventing the inhibition of p41Plk3 by PBD. We find that p41Plk3 is the activated form of Plk3 that regulates a feed-forward mechanism to promote apoptosis and suppress PDAC and metastasis. p41Plk3 phosphorylates c-Fos on Thr164, which in turn induces expression of Plk3 and pro-apoptotic genes. These findings uncover an NRDC-regulated post-translational mechanism that activates Plk3, establishing a prototypic regulation by scission mechanism.

The Hallmarks of Precancer.

Research on precancers, as defined as at-risk tissues and early lesions, is of high significance given the effectiveness of early intervention. We discuss the need for risk stratification to prevent overtreatment, an emphasis on the role of genetic and epigenetic aging when considering risk, and the importance of integrating macroenvironmental risk factors with molecules and cells in lesions and at-risk normal tissues for developing effective intervention and health policy strategies.

Clonal dominance defines metastatic dissemination in pancreatic cancer.

Tumors represent ecosystems where subclones compete during tumor growth. While extensively investigated, a comprehensive picture of the interplay of clonal lineages during dissemination is still lacking. Using patient-derived pancreatic cancer cells, we created orthotopically implanted clonal replica tumors to trace clonal dynamics of unperturbed tumor expansion and dissemination. This model revealed the multifaceted nature of tumor growth, with rapid changes in clonal fitness leading to continuous reshuffling of tumor architecture and alternating clonal dominance as a distinct feature of cancer growth. Regarding dissemination, a large fraction of tumor lineages could be found at secondary sites each having distinctive organ growth patterns as well as numerous undescribed behaviors such as abortive colonization. Paired analysis of primary and secondary sites revealed fitness as major contributor to dissemination. From the analysis of pro- and nonmetastatic isogenic subclones, we identified a transcriptomic signature able to identify metastatic cells in human tumors and predict patients' survival.

Oncogenic GNAS drives a gastric pylorus program in intraductal papillary mucinous neoplasms of the pancreas.

OBJECTIVE: Intraductal Papillary Mucinous Neoplasms (IPMNs) are cystic lesions and bona fide precursors for pancreatic ductal adenocarcinoma (PDAC). Recently, we showed that acinar to ductal metaplasia, an injury repair program, is characterized by a transcriptomic program similar to gastric spasmolytic polypeptide expressing metaplasia (SPEM), suggesting common mechanisms of reprogramming between the stomach and pancreas. The aims of this study were to assay IPMN for pyloric markers and to identify molecular drivers of this program. DESIGN: We analyzed RNA-seq studies of IPMN for pyloric markers, which were validated by immunostaining in patient samples. Cell lines expressing Kras G12D +/- GNAS R201C were manipulated to identify distinct and overlapping transcriptomic programs driven by each oncogene. A PyScenic-based regulon analysis was performed to identify molecular drivers in the pancreas. Expression of candidate drivers was evaluated by RNA-seq and immunostaining. RESULTS: Pyloric markers were identified in human IPMN. GNAS R201C drove expression of these markers in cell lines and siRNA targeting of GNAS R201C or Kras G12D demonstrates that GNAS R201C amplifies a mucinous, pyloric phenotype. Regulon analysis identified a role for transcription factors SPDEF, CREB3L1, and CREB3L4, which are expressed in patient samples. siRNA-targeting of Spdef inhibited mucin production. CONCLUSION: De novo expression of a SPEM phenotype has been identified in pancreatitis and a pyloric phenotype in Kras G12D -driven PanIN and Kras G12D ;GNAS R201C -driven IPMN, suggesting common mechanisms of reprogramming between these lesions and the stomach. A transition from a SPEM to pyloric phenotype may reflect disease progression and/or oncogenic mutation. IPMN-specific GNAS R201C amplifies a mucinous phenotype, in part, through SPDEF.

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-Specific Transcriptome and Molecular Subtype.

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predicted consensus molecular subtypes in patients with metastatic colorectal cancer. Analysis of plasma evRNA also enabled monitoring of changes in transcriptomic subtype under treatment selection pressure and identification of molecular pathways associated with recurrence. This approach also revealed expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of using transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to the identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. SIGNIFICANCE: The development of an approach to interrogate molecular subtypes, cancer-associated pathways, and differentially expressed genes through RNA sequencing of plasma extracellular vesicles lays the foundation for liquid biopsy-based longitudinal monitoring of patient tumor transcriptomes.

Genetic Deletion of Galectin-3 Inhibits Pancreatic Cancer Progression and Enhances the Efficacy of Immunotherapy.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) has a desmoplastic tumor stroma and immunosuppressive microenvironment. Galectin-3 (GAL3) is enriched in PDAC, highly expressed by cancer cells and myeloid cells. However, the functional roles of GAL3 in the PDAC microenvironment remain elusive. METHODS: We generated a novel transgenic mouse model (LSL-KrasG12D/+;Trp53loxP/loxP;Pdx1-Cre;Lgals3-/- [KPPC;Lgals3-/-]) that allows the genetic depletion of GAL3 from both cancer cells and myeloid cells in spontaneous PDAC formation. Single-cell RNA-sequencing analysis was used to identify the alterations in the tumor microenvironment upon GAL3 depletion. We investigated both the cancer cell-intrinsic function and immunosuppressive function of GAL3. We also evaluated the therapeutic efficacy of GAL3 inhibition in combination with immunotherapy. RESULTS: Genetic deletion of GAL3 significantly inhibited the spontaneous pancreatic tumor progression and prolonged the survival of KPPC;Lgals3-/- mice. Single-cell analysis revealed that genetic deletion of GAL3 altered the phenotypes of immune cells, cancer cells, and other cell populations. GAL3 deletion significantly enriched the antitumor myeloid cell subpopulation with high major histocompatibility complex class II expression. We also identified that GAL3 depletion resulted in CXCL12 upregulation, which could act as a potential compensating mechanism on GAL3 deficiency. Combined inhibition of the CXCL12-CXCR4 axis and GAL3 enhanced the efficacy of anti-PD-1 immunotherapy, leading to significantly inhibited PDAC progression. In addition, deletion of GAL3 also inhibited the basal/mesenchymal-like phenotype of pancreatic cancer cells. CONCLUSIONS: GAL3 promotes PDAC progression and immunosuppression via both cancer cell-intrinsic and immune-related mechanisms. Combined treatment targeting GAL3, CXCL12-CXCR4 axis, and PD-1 represents a novel therapeutic strategy for PDAC.

Ecological patterns and processes of temporal turnover within lung infection microbiota.

BACKGROUND: Chronic infection and consequent airway inflammation are the leading causes of morbidity and early mortality for people living with cystic fibrosis (CF). However, lower airway infections across a range of chronic respiratory diseases, including in CF, do not follow classical 'one microbe, one disease' concepts of infection pathogenesis. Instead, they are comprised of diverse and temporally dynamic lung infection microbiota. Consequently, temporal dynamics need to be considered when attempting to associate lung microbiota with changes in disease status. Set within an island biogeography framework, we aimed to determine the ecological patterns and processes of temporal turnover within the lung microbiota of 30 paediatric and adult CF patients prospectively sampled over a 3-year period. Moreover, we aimed to ascertain the contributions of constituent chronic and intermittent colonizers on turnover within the wider microbiota. RESULTS: The lung microbiota within individual patients was partitioned into constituent chronic and intermittent colonizing groups using the Leeds criteria and visualised with persistence-abundance relationships. This revealed bacteria chronically infecting a patient were both persistent and common through time, whereas intermittently infecting taxa were infrequent and rare; respectively representing the resident and transient portions of the wider microbiota. It also indicated that the extent of chronic colonization was far greater than could be appreciated with microbiological culture alone. Using species-time relationships to measure temporal turnover and Vellend's rationalized ecological processes demonstrated turnover in the resident chronic infecting groups was conserved and underpinned principally by the deterministic process of homogenizing dispersal. Conversely, intermittent colonizing groups, representing newly arrived immigrants and transient species, drove turnover in the wider microbiota and were predominately underpinned by the stochastic process of drift. For adult patients, homogenizing dispersal and drift were found to be significantly associated with lung function. Where a greater frequency of homogenizing dispersal was observed with worsening lung function and conversely drift increased with better lung function. CONCLUSIONS: Our work provides a novel ecological framework for understanding the temporal dynamics of polymicrobial infection in CF that has translational potential to guide and improve therapeutic targeting of lung microbiota in CF and across a range of chronic airway diseases. Video Abstract.

Impact of KRAS mutations and co-mutations on clinical outcomes in pancreatic ductal adenocarcinoma.

The relevance of KRAS mutation alleles to clinical outcome remains inconclusive in pancreatic adenocarcinoma (PDAC). We conducted a retrospective study of 803 patients with PDAC (42% with metastatic disease) at MD Anderson Cancer Center. Overall survival (OS) analysis demonstrated that KRAS mutation status and subtypes were prognostic (p < 0.001). Relative to patients with KRAS wildtype tumors (median OS 38 months), patients with KRASG12R had a similar OS (median 34 months), while patients with KRASQ61 and KRASG12D mutated tumors had shorter OS (median 20 months [HR: 1.9, 95% CI 1.2-3.0, p = 0.006] and 22 months [HR: 1.7, 95% CI 1.3-2.3, p < 0.001], respectively). There was enrichment of KRASG12D mutation in metastatic tumors (34% vs 24%, OR: 1.7, 95% CI 1.2-2.4, p = 0.001) and enrichment of KRASG12R in well and moderately differentiated tumors (14% vs 9%, OR: 1.7, 95% CI 1.05-2.99, p = 0.04). Similar findings were observed in the external validation cohort (PanCAN's Know Your Tumor® dataset, n = 408).

A Randomized Trial of Two Remote Health Care Delivery Models on the Uptake of Genetic Testing and Impact on Patient-Reported Psychological Outcomes in Families With Pancreatic Cancer: The Genetic Education, Risk Assessment, and Testing (GENERATE) Study.

BACKGROUND & AIMS: Genetic testing uptake for cancer susceptibility in family members of patients with cancer is suboptimal. Among relatives of patients with pancreatic ductal adenocarcinoma (PDAC), The GENetic Education, Risk Assessment, and TEsting (GENERATE) study evaluated 2 online genetic education/testing delivery models and their impact on patient-reported psychological outcomes. METHODS: Eligible participants had ≥1 first-degree relative with PDAC, or ≥1 first-/second-degree relative with PDAC with a known pathogenic germline variant in 1 of 13 PDAC predisposition genes. Participants were randomized by family, between May 8, 2019, and June 1, 2021. Arm 1 participants underwent a remote interactive telemedicine session and online genetic education. Arm 2 participants were offered online genetic education only. All participants were offered germline testing. The primary outcome was genetic testing uptake, compared by permutation tests and mixed-effects logistic regression models. We hypothesized that Arm 1 participants would have a higher genetic testing uptake than Arm 2. Validated surveys were administered to assess patient-reported anxiety, depression, and cancer worry at baseline and 3 months postintervention. RESULTS: A total of 424 families were randomized, including 601 participants (n = 296 Arm 1; n = 305 Arm 2), 90% of whom completed genetic testing (Arm 1 [87%]; Arm 2 [93%], P = .014). Arm 1 participants were significantly less likely to complete genetic testing compared with Arm 2 participants (adjusted ratio [Arm1/Arm2] 0.90, 95% confidence interval 0.78-0.98). Among participants who completed patient-reported psychological outcomes questionnaires (Arm 1 [n = 194]; Arm 2 [n = 206]), the intervention did not affect mean anxiety, depression, or cancer worry scores. CONCLUSIONS: Remote genetic education and testing can be a successful and complementary option for delivering genetics care. (Clinicaltrials.gov, number NCT03762590).

Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer.

BACKGROUND: Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response. CONTENT: The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes. SUMMARY: The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.

Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer.

PURPOSE: Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS: The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS: Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION: The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

A Small Molecule with Big Impact: MRTX1133 Targets the KRASG12D Mutation in Pancreatic Cancer.

KRAS mutations drive oncogenic alterations in numerous cancers, particularly in human pancreatic ductal adenocarcinoma (PDAC). About 93% of PDACs have KRAS mutations, with G12D (∼42% of cases) and G12V (∼32% of cases) being the most common. The recent approval of sotorasib (AMG510), a small-molecule, covalent, and selective KRASG12C inhibitor, for treating patients with non-small cell lung cancer represents a breakthrough in KRAS targeted therapy. However, there is a need to develop other much-needed KRAS-mutant inhibitors for PDAC therapy. Notably, Mirati Therapeutics recently developed MRTX1133, a small-molecule, noncovalent, and selective KRASG12D inhibitor through extensive structure-based drug design. MRTX1133 has demonstrated potent in vitro and in vivo antitumor efficacy against KRASG12D-mutant cancer cells, especially in PDAC, leading to its recent initiation of a phase I/II clinical trial. Here, we provide a summary of the recent advancements related to the use of MRTX1133 for treating KRASG12D-mutant PDAC, focusing on its efficacy and underlying mechanistic actions. In addition, we discuss potential challenges and future directions for MRTX1133 therapy for PDAC, including overcoming intrinsic and acquired drug resistance, developing effective combination therapies, and improving MRTX1133's oral bioavailability and target spectrum. The promising results obtained from preclinical studies suggest that MRTX1133 could revolutionize the treatment of PDAC, bringing about a paradigm shift in its management.

Protein biomarkers and alternatively methylated cell-free DNA detect early stage pancreatic cancer.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed at an advanced stage. Liquid biopsy approaches may facilitate detection of early stage PDAC when curative treatments can be employed. DESIGN: To assess circulating marker discrimination in training, testing and validation patient cohorts (total n=426 patients), plasma markers were measured among PDAC cases and patients with chronic pancreatitis, colorectal cancer (CRC), and healthy controls. Using CA19-9 as an anchor marker, measurements were made of two protein markers (TIMP1, LRG1) and cell-free DNA (cfDNA) pancreas-specific methylation at 9 loci encompassing 61 CpG sites. RESULTS: Comparative methylome analysis identified nine loci that were differentially methylated in exocrine pancreas DNA. In the training set (n=124 patients), cfDNA methylation markers distinguished PDAC from healthy and CRC controls. In the testing set of 86 early stage PDAC and 86 matched healthy controls, CA19-9 had an area under the receiver operating characteristic curve (AUC) of 0.88 (95% CI 0.83 to 0.94), which was increased by adding TIMP1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.06), LRG1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02) or exocrine pancreas-specific cfDNA methylation markers at nine loci (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02). In the validation set of 40 early stage PDAC and 40 matched healthy controls, a combined panel including CA19-9, TIMP1 and a 9-loci cfDNA methylation panel had greater discrimination (AUC 0.86, 95% CI 0.77 to 0.95) than CA19-9 alone (AUC 0.82; 95% CI 0.72 to 0.92). CONCLUSION: A combined panel of circulating markers including proteins and methylated cfDNA increased discrimination compared with CA19-9 alone for early stage PDAC.