JCO Precision Oncology Conversations

In this JCO Precision Oncology Article Insights episode, Natalie DelRocco summarizes "Genomic Risk Classifiers in Localized Prostate Cancer: Precise but Not Standardized" by Góes et al. published on September 10, 2025.

TRANSCRIPT

Natalie DelRocco: Hello and welcome to JCO Precision Oncology Article Insights. I'm your host, Natalie DelRocco, and today we will be discussing the editorial "Genomic Risk Classifiers in Localized Prostate Cancer: Precise but Not Standardized."

This editorial by Góes, Li, and Chehrazi-Raffle, and Janopaul-Naylor et al. describes genomic risk classifiers, or GRCs, for patients with localized prostate cancer. Like any risk prediction model, GRCs are intended to help identify groups of patients that may benefit from less intense or more intense anticancer therapy. Risk prediction tools can be difficult to bring into clinical practice; they require a lot of validation. And as the authors describe, GRCs in localized prostate cancer are no exception.

The authors of this editorial contextualize an article by Janopaul-Naylor et al., which attempts to retrospectively explore the clinical use of three available GRCs for localized prostate cancer: Decipher, Oncotype DX, and Prolaris. Each of these three GRCs is being used in clinical practice currently.

In the original article, all three GRCs were associated with less intense therapy being prescribed in practice. However, the editorial authors note that this is likely selection bias due to the observational nature of the study design. It is conceivable that GRCs were more likely ordered to make decisions for patients who were already thought to be good candidates for less intensive therapy.

Another weakness of the retrospective study design is that patient level covariates known to be associated with clinical prognosis in localized prostate cancer, such as staging, Gleason score, prostate specific antigen, were unavailable. The authors note that sampling bias may also be an issue. Uninsured patients are not included in the original article, and therefore may impede the ability to make conclusions about the association of GRC use with income level.

The editorial authors highlight important study findings as well as these limitations, such as the heterogeneity of interventions following GRC result return. The Prolaris GRC was found to be associated with more surgical interventions, while the Decipher GRC was associated with more androgen deprivation therapy plus radiation. Additionally, patients with active surveillance were more likely to have a GRC in general ordered.

While these conclusions are very interesting, the editorial authors note that further exploration and validation, given the retrospective study design and limitations outlined, are needed to fully understand the impact of GRCs in the practice of treating localized prostate cancer.

Thank you for listening to JCO Precision Oncology Article Insights. Don't forget to give us a rating or a review and be sure to subscribe so that you never miss an episode. You can find all ASCO shows atasco.org/podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this episode of JCO PO Article Insights, host Dr. Jiasen He summarizes the article, "Somatic Mutation Profiles of Colorectal Cancer by Birth Cohort" by Gilad, et al published October 11, 2025.

TRANSCRIPT

Jiasen He: Hello, and welcome to the JCO Precision Oncology Article Insights. I am your host, Jiasen He, and today, we will be discussing the JCO Precision Oncology article, "Somatic Mutation Profiles of Colorectal Cancer by Birth Cohort," by Dr. Gilad and colleagues.

Early-onset colorectal cancer is defined as colorectal cancer diagnosed before the age of 50. Several reports have suggested that early-onset colorectal cancer has unique characteristics. Compared with late-onset colorectal cancer, early-onset colorectal cancer cases are more commonly found in the distal colon or rectum, tend to be diagnosed at more advanced stages, and may display unfavorable histologic features.

Although the overall incidence of colorectal cancer has declined in recent decades, the incidence of early-onset colorectal cancer continues to rise. This increase appears to be driven by birth cohort effects. The reasons behind this rise remain unclear but are likely multifactorial, involving changes in demographics, diet, lifestyle, environmental exposures, and genetic predisposition. At the same time, studies have shown conflicting results regarding whether there are differences in the mutation profiles between early-onset and late-onset colorectal cancer. Therefore, it is crucial to explore whether colorectal cancer somatic mutational landscape differs across birth cohorts, as this could provide important insight into generational shifts in colorectal cancer incidence.

To address this question, the authors conducted a retrospective study to characterize the mutation spectrum of colorectal cancer across different birth cohorts. Consecutive colorectal cancer patients who underwent somatic next-generation sequencing at the University of Chicago pathology laboratory between 2015 and 2022 were retrospectively identified. Tumors were tested for 154 to 168 genes and categorized as either microsatellite stable or high according to established thresholds. Patients with hereditary cancer syndromes or inflammatory bowel disease were excluded. Participants were then grouped into birth cohorts by decades, as well as into two major groups: those born before 1960 and after 1960. Genes that were identified in at least 5% of the sample were selected and grouped into 10 canonical cancer signaling pathways. These genes and pathways were then included in the analysis to explore their association with colorectal cancer across different birth cohorts and age groups.

A total of 369 patients were included in the study, with a median birth year of 1955 and a median age at colorectal cancer diagnosis of 62.9 years. 5.4% were identified as having microsatellite-high tumors. The median tumor mutational burden was 5 mutations per megabase for microsatellite-stable tumors and 57.7 mutations per megabase for microsatellite-high tumors. Patients with microsatellite-high tumors tended to have earlier birth years and were diagnosed at an older age. However, after adjusting for potential confounders, neither birth year nor age remained statistically significant. Similarly, after controlling for confounders, no significant associations were observed between birth year or age and mutation burden.

In this cohort, APC, TP53, and KRAS were the most frequently mutated genes. No statistically significant differences in the prevalence of gene mutations were observed across birth cohorts. Correspondingly, the most affected signaling pathways were the Wnt, TP53, and (RTK)/RAS pathways. Similar to the gene-level finding, no significant differences in the prevalence of these pathways were identified among birth cohorts.

When examining patients born before and after 1960, the authors found that the older birth cohorts were diagnosed at an older age and had higher tumor mutational burden. However, no significant differences were observed in any of the genes or pathways analyzed. Among microsatellite-stable tumors, 18.3% were classified as early-onset colorectal cancer, while 81.1% were late-onset colorectal cancer. Consistent with previous reports, early-onset colorectal cancers in this cohort were more likely to be left-sided and more common among more recent birth cohorts. However, no significant differences were identified in any of the examined genes or pathways when comparing early-onset to late-onset colorectal cancer.

In this cohort, a higher prevalence of early-onset colorectal cancer was observed among more recent birth cohorts, consistent with previous reports. Still, no distinct mutational signature was identified between the early and late birth cohorts. The authors proposed that the lack of distinct mutational profile by age or birth cohort may be due to the limited number of key molecular pathways driving colorectal cancer. Although environmental exposures likely differ across generations, the downstream effects may have converged on similar biological mechanisms, leading to comparable somatic mutations across cohorts. Alternately, they proposed that the observed birth cohort differences in colorectal incidence may be driven by distinct mutation signatures, epigenetic alterations, or changes in the immune microenvironment rather than variations in canonical gene mutations.

As the authors noted, given the retrospective nature of this study, its modest sample size, and the predominance of advanced-stage tumors, larger prospective studies are needed to validate these findings.

In summary, this study found no significant differences in the mutational landscape of colorectal cancer across birth cohorts or age groups. The authors proposed that the generational shift in colorectal cancer incidence is unlikely to be driven by changes in the underlying tumor genomics. However, larger prospective studies are needed to validate these findings.

Thank you for tuning in to JCO Precision Oncology Article Insights. Do not forget to subscribe and join us next time as we explore more groundbreaking research shaping the future of oncology.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO Precision Oncology Article Insights episode, Dr. Jiasen He summarizes JCO PO article "Synthetic Lethal Co-Mutations in DNA Damage Response Pathways Predict Response to Immunotherapy in Pan-Cancer" by Hua Zhong et al.

TRANSCRIPT

Jiasen He: Hello and welcome to the JCO Precision Oncology Article Insights. I am your host, Jiasen He, and today we will be discussing the JCO Precision Oncology article, "Synthetic Lethal Co-mutations in DNA Damage Response Pathway Predict Response to Immunotherapy in Pan-Cancer" by Dr. Zhang and colleagues.

Immunotherapy has emerged as a groundbreaking treatment option for many types of cancer. However, the overall response rate to immunotherapy is low, around 10% to 30%. This highlights the critical need to identify which patients are most likely to benefit from immunotherapy. Two of the most extensively studied biomarkers are PD-L1 expression and tumor mutation burden (TMB). High levels of PD-L1 and TMB have been associated with better response to immune checkpoint inhibitors, which are now widely used in clinical practice. The predictive value of these markers is inconsistent across all settings. Some tumors with high PD-L1 or TMB still respond poorly to immunotherapy.

One reason is that TMB reflects new antigen production, but recent studies suggest that new antigen levels do not always correlate with tumor immunogenicity. Many new antigens are not effectively recognized by T cells, limiting the immune response. Emerging evidence indicates that mutations in the DNA damage response (DDR) pathway play a critical role in moderating tumor immune interactions. Tumors harboring DDR pathways frequently exhibit increased genome instability, which may enhance their sensitivity to immune checkpoint inhibitors. While all these pathways are under active investigation, the optimal DDR pathway biomarkers for patient selection remain unclear.

Notably, tumor cells with a defect in one DDR pathway may acquire greater reliance on alternative DDR pathways. Recent studies suggest that synthetic lethal co-mutations within DDR pathways are associated with immune-inflamed or hot tumor microenvironments. Based on this rationale, Dr. Zhang is investigating if synthetic lethal co-mutations in DDR pathway response pathway can serve as a treatment biomarker for immune checkpoint inhibitors. To address this question, Dr. Zhang and colleagues first utilized SynLethDB 2.0, a comprehensive database that integrated multiple data sets.

Synthetic lethal (SL) gene pairs in this resource are identified through both experimental and computational approaches, with confidence scores assigned to each pair. These SL pairs were then mapped to gene sequencing results from several clinical cohorts. SL co-mutation status was defined as positive when both genes in a synthetic lethal pair were mutated. From this, SL co-mutation pairs specifically involving DDR pathway genes were selected. Patients were classified as DDR co-mutation positive if both genes in a synthetic lethal pair, each belonging to the defined DDR pathways, were mutated.

In total, 431 DDR-related SL pairs were identified and matched to sequencing data from clinical cohorts. Clinical information was extracted from the cBioPortal, while further analysis of immune infiltration was performed using DNA mutation and RNA expression data from The Cancer Genome Atlas (TCGA) pan-cancer data set. The author first examined the correlation between SL co-mutation status and response to ICI therapy. They discovered that patients with SL co-mutation showed significantly improved outcome to ICI therapy across various clinical cohorts.

Notably, in patients who did not receive ICI treatment, patients with SL co-mutation showed markedly compromised overall survival. Further analysis focused on the predictive value of SL co-mutation within DDR pathway genes. The author found that patients with DDR SL co-mutation had a longer overall survival compared to those with mutations in a single DDR gene, implying that SL co-mutations may be more effective biomarkers within the DDR pathway.

To explore this further, in the TMB-MSKCC cohort, the author found that patients with DDR co-mutation constituted approximately 20% of various cancer types, including non-small cell lung cancer, melanoma, and bladder cancer. These patients demonstrated significantly better survival outcomes and disease control rates when treated with ICIs compared to DDR co-mutation negative patients. Notably, the TMB level was substantially higher in patients with DDR co-mutation, a finding consistent with data from the Miao-lung cohort.

Furthermore, in cohorts not treated with ICIs, patients with DDR co-mutation had a shorter overall survival compared to their counterparts. Upon stratifying by PD-L1 expression, the author observed that patients with DDR co-mutation who were also PD-L1 positive derived the greatest clinical benefit from ICI therapy. Upon analyzing the frequency of co-mutation within the DDR pathway, the authors found that patients with SL co-mutation in the CPF-CPF pathway experienced remarkable survival benefit from ICIs. Within this group, one of the most common co-mutation combinations was TP53-ATM, observed in approximately 45% of cases, which was associated with a better response to ICI therapy.

Further analysis of immune cell infiltration revealed that patients with TP53-ATM co-mutation exhibited a distinct tumor immune microenvironment. As the authors stated, the study's main limitation lies in the nature of retrospective analysis, which lacked the control over confounding variables and was subject to non-random sampling. For instance, patients with both SL co-mutations and DDR SL co-mutations exhibited high TMB, and TMB was known to be associated with improved response to ICI therapy itself. So, these findings require validation through prospective studies, and immune infiltration analysis needs confirmation via laboratory experiments.

In conclusion, the authors found that patients with SL co-mutations in DDR pathways showed favorable clinical response and prolonged survival following ICI therapy. They also identified TP53-ATM co-mutations as a clinically relevant biomarker for predicting ICI treatment response.

Thank you for tuning in to JCO Precision Oncology Article Insights. Don't forget to subscribe and join us next time as we explore more groundbreaking research shaping the future of oncology.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO PO Article insights episode, Dr. Jiasen He summarized the JCO PO article "Mucin 16–Directed Therapy in Pediatric Sarcomas: Case Evidence of Ubamatamab Efficacy in Epithelioid Sarcoma and Its Implications for Other Sarcoma Subtypes" by Connolly et al.

TRANSCRIPT

Jiasen He: Hello, and welcome to JCO Precision Oncology Article Insights. I'm your host, Jiasen He, and today we'll be discussing the JCO Precision Oncology article, "Mucin 16-Directed Therapy in Pediatric Sarcomas: Case Evidence of Ubamatamab Efficacy in Epithelioid Sarcoma and Its Implication for Other Sarcoma Subtypes" by Connolly et al.

Epithelioid sarcoma and malignant rhabdoid tumor are rare pediatric soft tissue sarcomas, characterized by INI1 loss, high recurrence rates, and poor outcome despite multimodal treatments. Emerging evidence has shown that Mucin 16 is expressed in both tumor types. Mucin 16 is a transmembrane glycoprotein whose extracellular domain can be cleaved and released as CA-125. Both Mucin 16 and CA-125 are well-established biomarkers in several adult epithelioid malignancies, particularly ovarian cancer. Ubamatamab is a specific T-cell engager targeting CD3 and Mucin 16. It has demonstrated antitumor activity in patients with recurrent ovarian cancer, and clinical trials are ongoing to evaluate its efficacy as monotherapy or in combination regimens.

In this manuscript, Connolly et al. present the first reported case of a heavily pretreated patient with epithelioid sarcoma who responded to ubamatamab, followed by an investigation into mechanisms of resistance after disease progression. Furthermore, the authors retrospectively assessed Mucin 16 expression in a cohort of pediatric and young adult sarcomas, finding high expression in both epithelioid sarcoma and malignant rhabdoid tumor.

In this case report, the authors describe a 23-year-old woman with relapsed metastatic epithelioid sarcoma. Initially diagnosed at age 12, she had received multiple lines of treatments, including surgery, radiotherapy, targeted therapy, and immunotherapy. Following disease progression after all these treatments, her tumor was tested for Mucin 16 expression and it demonstrated 100% positivity with markedly elevated CA-125 levels, providing a rationale for treatment with the Mucin 16-CD3 bispecific T-cell engager, ubamatamab.

Ubamatamab was administered in an escalating dose schedule up to 250 mg once weekly during cycle one and continued for a total of 162 weeks. The best response was observed at week 11, with a 40% reduction and a marked decline in CA-125 levels. Disease progression was first detected in a single left lower lobe lung nodule, which on biopsy showed a reduction in Mucin 16 expression from 100% to less than 5%. Post-treatment analysis revealed changes in the tumor microenvironment, including increased expression of T-cell exhaustion markers such as PD-1 and LAG-3.

Ubamatamab was generally well tolerated. Cytokine release syndrome occurred during the escalating phase of cycle one, presenting with fever and hypoxia. Other notable adverse events included pleural and pericardial effusion, both of which resolved spontaneously. Given its favorable safety profile and limited alternative treatment options, ubamatamab was continued beyond the initial progression. The patient ultimately received 28 cycles of treatment before she passed away due to disease progression.

In the second part of the paper, the authors examined Mucin 16 expression in a cohort of pediatric and young adult sarcomas. Among 91 samples, Mucin 16 was expressed in six out of eight epithelioid sarcomas and two out of four malignant rhabdoid tumors. H-score analysis showed that all Mucin 16-positive tumors showed moderate to high expression levels.

In conclusion, this manuscript presents the first reported use of a Mucin 16-CD3 bispecific T-cell engager for epithelioid sarcoma, along with an investigation into resistance mechanisms following progression. The treatment achieved a substantial partial response with a favorable safety profile. The findings suggest that resistance may be associated with loss of Mucin 16 expression and T-cell exhaustion. Follow-up studies are needed to confirm these mechanisms. Notably, the study also identifies INI1-deficient sarcoma as a group with high Mucin 16 expression, warranting additional validation and mechanism exploration. These findings offer valuable insight for future therapeutic strategies and support the use of Mucin 16/CA-125 as both a treatment target and a biomarker for patient selection and disease monitoring.

Thank you for tuning in to JCO Precision Oncology Article Insights. Don't forget to subscribe and join us next time as we explore more groundbreaking research shaping the future of oncology.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO Precision Oncology Article Insights episode, Natalie DelRocco summarizes "Prognostic Value of the G2 Expression Signature and MYC Overexpression in Childhood High-Grade Osteosarcoma" by Roelof van Ewijk et al. published on May 29, 2025.

TRANSCRIPT

Natalie Del Rocco: Hello, and welcome to JCO Precision Oncology Article Insights. I'm your host, Natalie DelRocco, and today we will be discussing the original report, "Prognostic Value of the G2 Expression Signature and MYC Overexpression in Childhood High-Grade Osteosarcoma." This original report by van Ewijk et al. describes a study of the association between 2 biomarkers and survival outcomes among patients with high-grade osteosarcoma. Osteosarcoma is a disease where not much progress has been made in risk stratification factors that could potentially help patients target lower-risk therapies, less toxic therapies, or therapies that might be more toxic but could help their high-risk osteosarcoma.

So, it's important to identify risk factors that can help target therapies. The G1/G2 gene expression signature is a prognostic risk score developed by a French osteosarcoma group in 2022. They showed in a cohort of 79 osteosarcoma patients that risk score was associated with poorer event-free survival and overall survival. This considers expression of 15 individual genes. MYC amplification was shown in 2023 by a North American osteosarcoma group to be associated with poor overall survival in a cohort of 92 osteosarcoma patients, and this group validated that finding in a localized cohort in the same publication.

The goal of this particular original report was to assess the prognostic significance of each of these biomarkers in a population independent to those prior publications and, hence, to serve as an external validation of prior findings and to assess these 2 biomarkers in the same study. The investigators considered MYC amplification, defined as having greater than 7 copies; MYC expression as a continuous rather than the previously categorized variable; and G2 expression defined as a continuous variable; and then G2 expression defined as a dichotomous variable with the cut point at the median, as done in the original paper.

What the investigators found in their primary multivariable Cox proportional hazards regression model, which controlled for additional clinical risk factors such as age, tumor site, tumor size, is that G2 expression and MYC expression as continuous variables were associated with increased hazard of EFS and OS event. MYC amplification was not found to be prognostic. This is not surprising. When we have continuous variables, we have greater statistical power, we decrease the likelihood that an identified cut point in a previous study does not generalize well to either our genetic assay or our patient population. So, we don't have to worry about finding the optimal cut point in our particular patient sample.

Thank you for listening to our JCO Precision Oncology Article Insights. Don't forget to give us a rating or review, and be sure to like and subscribe so that you never miss an episode. You can find all ASCO shows at asco.org\podcasts.

The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.

Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.