Plasma Methylated DNA Markers for Melanoma Surveillance

PURPOSE

Surveillance after primary melanoma treatment aims to detect early signs of low-volume systemic disease. The current standard of care, surveillance imaging, is costly and difficult to access. We therefore sought to develop methylated DNA markers (MDMs) as promising alternatives for disease surveillance.

METHODS

We used reduced representation bisulfite sequencing (RRBS) to identify MDMs in DNA samples obtained from metastatic melanoma, benign nevi, and normal skin tissues. The identified MDMs underwent validation in an independent cohort of tissue and buffy coat DNA samples. Subsequently, we tested the validated MDMs in the plasma DNA of patients with metastatic melanoma undergoing surveillance with total body imaging and compared them with cancer-free controls. To estimate the overall predictive accuracy of the MDMs, we used random forest modeling with bootstrap cross-validation.

RESULTS

Forty MDMs demonstrated discrimination between melanoma cases and controls consisting of benign nevi and normal skin. Nine MDMs passing biological validation in tissue were run on 77 plasma samples from individuals with a history of metastatic melanoma, 49 of whom had evidence of disease detected by imaging at the time of blood draw, and 100 cancer-free controls. The cross-validated sensitivity of the panel for imaging-positive disease was 80% with a specificity of 100% in cancer-free controls, resulting in an overall AUC of 0.88 (95% CI, 0.81 to 0.96). The survival estimates for patients with melanoma who tested positive for the panel at 6 months and 1 year were 67% and 56%, respectively, while those who tested negative had survival rates of 100% and 92%.

CONCLUSION

MDMs identified by RRBS demonstrate a high degree of concordance with imaging results in the plasma of patients with metastatic melanoma. Further prospective studies in larger intended use cohorts are needed to confirm these findings.

Abstract 631: Validation of a panel of methylated DNA and protein markers for multi-cancer detection in plasma

Purpose: Many cancer deaths could be avoided, and survival could be improved with detection of cancer at an earlier stage. Screening programs for breast, colon, and cervical cancer as well as the NLST trial for lung cancer screening demonstrated significant improvement in survival rates with screening. However, for 2021, the American Cancer Society estimates these screened cancers represent less than ~40% of cancer incidence and deaths. The remainder of cancer deaths occur because of tumors in unscreened organs and, therefore, a multicancer test that detects cancer in these organs can increase survival rates. By focusing on detection of unscreened cancers, this type of multicancer test would be complementary to current screening procedures. Here we describe the validation of a combined panel of methylated DNA markers (MDMs) and proteins for multicancer detection through testing an independent set of case/control samples.

Experimental Procedures: In this study, we further evaluate the performance of our previously identified panel of 15 MDMs and 5 proteins for multicancer detection (Allawi et al., 2021 AACR Annual Meeting) by testing 315 controls and 160 cases encompassing 6 cancer types (liver, esophageal, lung, ovarian, pancreatic, and stomach). All samples used in the study were case-control collections with smoking status, age, and gender matching between cases and asymptomatic controls. Testing was performed in blinded fashion using multiplex PCR followed by LQAS (Long probe Quantitative Amplified Signal) assay on bisulfite converted DNA extracted from 3 mL of plasma collected in LB Gard® blood tubes. Protein concentrations were determined from paired serum aliquots and combined with MDMs for a multi-analyte analysis. The subjects were divided into training and validation with equal representation of cancer type, staging, gender, and age. Two thirds of the cases and controls were used to train with a logistic prediction algorithm, and the remaining 1/3 were used to validate the model.

Results: Using stepwise logistic regression, a training model of MDMs and protein markers resulted in an area under the receiver operating characteristics curve (AUC) of 0.97 and cancer sensitivity of 89% at 98% specificity. The same model predicted the validation set with an AUC of 0.96 and cancer sensitivity of 85% at a specificity of 95%. Applying the algorithm to the combined training and validation sets resulted in sensitivities and specificities of 88% and 97%, respectively. The sensitivities per cancer type ranged from 73% for pancreatic cancer to 97% for lung cancer.

Conclusion and Next Steps: This study demonstrates the performance of our MDMs and protein markers and their importance as components in our multi-omics strategy for multicancer detection. The next steps would be to expand the testing to include additional cancer types and combine with NGS-based methods to improve performance and optimize workflow.

Citation Format: Hatim T. Allawi, Slava Katerov, Abram Vaccaro, Harrison L. Fleming, Debra E. Rugowski, Brittany Otto, Justin Heilberger, Jillian Cassel, Jacquelyn Hennek, William Taylor, Graham Lidgard. Validation of a panel of methylated DNA and protein markers for multi-cancer detection in plasma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 631.

Plasma methylated DNA markers of cutaneous melanoma: Association with PET/CT-positive disease

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Background: Cutaneous melanoma surveillance is important to identify low-volume systemic disease, but imaging is costly and poorly accessible to patients; frequent skin checks lack sensitivity and specificity. We aimed to establish clinical feasibility of a liquid biopsy blood test, which quantifies validated, melanoma-specific, methylated DNA markers (MDMs), previously discovered, and reported by our team, using tissue extracted DNA. Methods: We prospectively collected blood from adult patients with histologically confirmed melanoma metastases and no other internal malignancies (within 5-years) who underwent surveillance by FDG-PET/CT (N = 88). Blood from age- and sex balanced cancer-free controls (N = 100) were compared. From PET/CT, we extracted the number of organs involved, SUV-max, and largest tumor diameter. Unequivocal metastasis was defined as SUV ≥ 4 and largest diameter > 5 mm. Because PET/CT is inadequate for the screening of brain metastases, we excluded the brain from the analysis. MDMs ( chr11.149, HOXA9, chr20.210, FLJ22536, CLIC5, SIX4, chr7.155, chr17.730, chr1.110) were assayed using target enrichment long-probe quantitative-amplified signal assays, normalized to B3GALT6, in blinded fashion. Using a logistic regression approach and nine candidate MDMs, we calculated the sensitivity for detecting patients with metastasis on PET/CT at 100% specificity. Results: 52/88 (59%) of melanoma patients showed evidence of metastasis on PET/CT at the time of blood draw. At 100% specificity, a panel of 4 MDMs ( HOXA9, chr20.210, chr17.730, chr1.110) yielded a sensitivity of 86.5% (45/52 cases) vs. 100 cancer-free controls. When applying this model to the 36 PET/CT-negative patients, specificity was as high as 97.2% (35/36 cases) while maintaining a sensitivity of 86.5% (one patient with a positive test result had a complete metabolic response to binimetinib / encorafenib prior to negative PET/CT). For patients with ≥ 2 organs involved by metastasis, sensitivity was 100% (29/29 cases). False-negative cases had metastasis in single organs and were characterized by minimal tumor burden and oral corticosteroid use. One false-negative patient had localized stage III disease without known primary melanoma. Conclusions: Plasma MDM levels appear highly concordant with FDG-PET/CT in patients with metastatic cutaneous melanoma. A liquid biopsy approach has potential to lower cost and improve patient access to surveillance. Additional prospective studies in larger intended use cohorts are needed to validate our results.

Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast

Microbes can be metabolically engineered to produce biofuels and biochemicals, but rerouting metabolic flux toward products is a major hurdle without a systems-level understanding of how cellular flux is controlled. To understand flux rerouting, we investigated a panel of Saccharomyces cerevisiae strains with progressive improvements in anaerobic fermentation of xylose, a sugar abundant in sustainable plant biomass used for biofuel production. We combined comparative transcriptomics, proteomics, and phosphoproteomics with network analysis to understand the physiology of improved anaerobic xylose fermentation. Our results show that upstream regulatory changes produce a suite of physiological effects that collectively impact the phenotype. Evolved strains show an unusual co-activation of Protein Kinase A (PKA) and Snf1, thus combining responses seen during feast on glucose and famine on non-preferred sugars. Surprisingly, these regulatory changes were required to mount the hypoxic response when cells were grown on xylose, revealing a previously unknown connection between sugar source and anaerobic response. Network analysis identified several downstream transcription factors that play a significant, but on their own minor, role in anaerobic xylose fermentation, consistent with the combinatorial effects of small-impact changes. We also discovered that different routes of PKA activation produce distinct phenotypes: deletion of the RAS/PKA inhibitor IRA2 promotes xylose growth and metabolism, whereas deletion of PKA inhibitor BCY1 decouples growth from metabolism to enable robust fermentation without division. Comparing phosphoproteomic changes across ira2Δ and bcy1Δ strains implicated regulatory changes linked to xylose-dependent growth versus metabolism. Together, our results present a picture of the metabolic logic behind anaerobic xylose flux and suggest that widespread cellular remodeling, rather than individual metabolic changes, is an important goal for metabolic engineering.

Ecological and Genetic Barriers Differentiate Natural Populations of Saccharomyces cerevisiae

How populations that inhabit the same geographical area become genetically differentiated is not clear. To investigate this, we characterized phenotypic and genetic differences between two populations of Saccharomyces cerevisiae that in some cases inhabit the same environment but show relatively little gene flow. We profiled stress sensitivity in a group of vineyard isolates and a group of oak-soil strains and found several niche-related phenotypes that distinguish the populations. We performed bulk-segregant mapping on two of the distinguishing traits: The vineyard-specific ability to grow in grape juice and oak-specific tolerance to the cell wall damaging drug Congo red. To implicate causal genes, we also performed a chemical genomic screen in the lab-strain deletion collection and identified many important genes that fell under quantitative trait loci peaks. One gene important for growth in grape juice and identified by both the mapping and the screen was SSU1, a sulfite-nitrite pump implicated in wine fermentations. The beneficial allele is generated by a known translocation that we reasoned may also serve as a genetic barrier. We found that the translocation is prevalent in vineyard strains, but absent in oak strains, and presents a postzygotic barrier to spore viability. Furthermore, the translocation was associated with a fitness cost to the rapid growth rate seen in oak-soil strains. Our results reveal the translocation as a dual-function locus that enforces ecological differentiation while producing a genetic barrier to gene flow in these sympatric populations.