We aimed to assess the concordance of colorectal cancer-associated methylated DNA markers (MDM) in primary and metastatic colorectal cancer for feasibility in detection of distantly ...recurrent/metastatic colorectal cancer in plasma.
A panel of previously discovered colorectal cancer-associated MDMs was selected. MDMs from primary and paired metastatic colorectal cancer tissue were assayed with quantitative methylation-specific PCR. Plasma MDMs were measured blindly by target enrichment long-probe quantitative-amplified signal assays. Random forest modeling was used to derive a prediction algorithm of MDMs in archival plasma samples from primary colorectal cancer cases. This algorithm was validated in prospectively collected plasma samples from recurrent colorectal cancer cases. The accuracy of the algorithm was summarized as sensitivity, specificity, and area under the curve (AUC).
Of the 14 selected MDMs, the concordance between primary and metastatic tissue was considered moderate or higher for 12 MDMs (86%). At a preset specificity of 95% (91%-98%), a panel of 13 MDMs, in plasma from 97 colorectal cancer cases and 200 controls, detected stage IV colorectal cancer with 100% (80%-100%) sensitivity and all stages of colorectal cancer with an AUC of 0.91 (0.87-0.95), significantly higher than carcinoembryonic antigen AUC, 0.72 (0.65-0.79). This panel, in plasma from 40 cases and 60 healthy controls, detected recurrent/metastatic colorectal cancer with 90% (76%-97%) sensitivity, 90% (79%-96%) specificity, and an AUC of 0.96 (0.92-1.00). The panel was positive in 0.30 (0.19-0.43) of 60 patients with no evidence of disease in post-operative patients with colorectal cancer.
Plasma assay of novel colorectal cancer-associated MDMs can reliably detect both primary colorectal cancer and distantly recurrent colorectal cancer with promising accuracy.
We have previously identified tissue methylated DNA markers (MDMs) associated with pancreatic ductal adenocarcinoma (PDAC). In this case-control study, we aimed to assess the diagnostic performance ...of plasma MDMs for PDAC.
Thirteen MDMs (
, and
) were identified on the basis of selection criteria applied to results of prior tissue experiments and assays were optimized in plasma. Next, 340 plasma samples (170 PDAC cases and 170 controls) were assayed using target enrichment long-probe quantitative amplified signal method. Initially, 120 advanced-stage PDAC cases and 120 healthy controls were used to train a prediction algorithm at 97.5% specificity using random forest modeling. Subsequently, the locked algorithm derived from the training set was applied to an independent blinded test set of 50 early-stage PDAC cases and 50 controls. Finally, data from all 340 patients were combined, and cross-validated.
The cross-validated area under the receiver operating characteristic curve (AUC) for the training set was 0.93 (0.89-0.96) for the MDM panel alone, 0.91 (95% confidence interval, 0.87-0.96) for carbohydrate antigen 19-9 (CA19-9) alone, and 0.99 (0.98-1) for the combined MDM-CA19-9 panel. In the test set of early-stage PDAC, the AUC for MDMs alone was 0.84 (0.76-0.92), CA19-9 alone was 0.87 (0.79-0.94), and combined MDM-CA19-9 panel was 0.90 (0.84-0.97) significantly better compared with either MDMs alone or CA19-9 alone (
= 0.0382 and 0.0490, respectively). At a preset specificity of 97.5%, the sensitivity for the combined panel in the test set was 80% (28%-99%) for stage I disease and 82% (68%-92%) for stage II disease. Using the combined datasets, the cross-validated AUC was 0.9 (0.86-0.94) for the MDM panel alone and 0.89 for CA19-9 alone (0.84-0.93) versus 0.97 (0.94-0.99) for the combined MDM-CA19-9 panel (
≤ 0.0001). Overall, cross-validated sensitivity of MDM-CA19-9 panel was 92% (83%-98%), with an observed specificity of 92% at the preset specificity of 97.5%.
Plasma MDMs in combination with CA19-9 detect PDAC with significantly higher accuracy compared with either biomarker individually.
Radiographic surveillance of colorectal cancer (CRC) after curative-intent therapy is costly and unreliable. Methylated DNA markers (MDMs) detected primary CRC and metastatic recurrence with high ...sensitivity and specificity in cross-sectional studies. This study evaluated using serial MDMs to detect recurrence and monitor the treatment response to anti-cancer therapies.
A nested case-control study was drawn from a prospective cohort of patients with CRC who completed curative-intent therapy for CRC of all stages. Plasma MDMs were assayed vis target enrichment long-probe quantitative-amplified signal assays, normalized to
, and analyzed in combination with serum carcinoembryonic antigen to yield an MDM score. Clinical information, including treatment and radiographic measurements of the tumor burden, were longitudinally collected.
Of the 35 patients, 18 had recurrence and 17 had no evidence of disease during the study period. The MDM score was positive in 16 out of 18 patients who recurred and only 2 of the 17 patients without recurrence. The MDM score detected recurrence in 12 patients preceding clinical or radiographic detection of recurrent CRC by a median of 106 days (range 90-232 days).
Plasma MDMs can detect recurrent CRC prior to radiographic detection; this tumor-agnostic liquid biopsy approach may assist cancer surveillance and monitoring.
Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC ...susceptibility genes. Accurate assessment of risk factor status is provider knowledge-dependent and requires extensive manual chart review by experts. Natural Language Processing (NLP) has shown promise in automated data extraction from the electronic health record (EHR). We aimed to use NLP for automated extraction of PDAC risk factors from unstructured clinical notes in the EHR.
We first developed rule-based NLP algorithms to extract PDAC risk factors at the document-level, using an annotated corpus of 2091 clinical notes. Next, we further improved the NLP algorithms using a cohort of 1138 patients through patient-level training, validation, and testing, with comparison against a pre-specified reference standard. To minimize false-negative results we prioritized algorithm recall.
In the test set (n = 807), the NLP algorithms achieved a recall of 0.933, precision of 0.790, and F1-score of 0.856 for family history of PDAC. For germline genetic mutations, the algorithm had a high recall of 0.851, while precision and F1-score were lower at 0.350 and 0.496 respectively. Most false positives for germline mutations resulted from erroneous recognition of tissue mutations.
Rule-based NLP algorithms applied to unstructured clinical notes are highly sensitive for automated identification of PDAC risk factors. Further validation in a large primary-care patient population is warranted to assess real-world utility in identifying HRIs for pancreatic cancer screening.
Aberrant DNA methylation is an early event in carcinogenesis which could be leveraged to detect ovarian cancer (OC) in plasma.
DNA from frozen OC tissues, benign fallopian tube epithelium (FTE), and ...buffy coats from cancer-free women underwent reduced representation bisulfite sequencing (RRBS) to identify OC MDMs. Candidate MDM selection was based on receiver operating characteristic (ROC) discrimination, methylation fold change, and low background methylation among controls. Blinded biological validation was performed using methylated specific PCR on DNA extracted from independent OC and FTE FFPE tissues. MDMs were tested using Target Enrichment Long-probe Quantitative Amplified Signal (TELQAS) assays in pre-treatment plasma from women newly diagnosed with OC and population-sampled healthy women. A random forest modeling analysis was performed to generate predictive probability of disease; results were 500-fold in silico cross-validated.
Thirty-three MDMs showed marked methylation fold changes (10 to >1000) across all OC subtypes vs FTE. Eleven MDMs (GPRIN1, CDO1, SRC, SIM2, AGRN, FAIM2, CELF2, RIPPLY3, GYPC, CAPN2, BCAT1) were tested on plasma from 91 women with OC (73 (80%) high-grade serous (HGS)) and 91 without OC; the cross-validated 11-MDM panel highly discriminated OC from controls (96% (95% CI, 89–99%) specificity; 79% (69–87%) sensitivity, and AUC 0.91 (0.86–0.96)). Among the 5 stage I/II HGS OCs included, all were correctly identified.
Whole methylome sequencing, stringent filtering criteria, and biological validation yielded candidate MDMs for OC that performed with high sensitivity and specificity in plasma. Larger plasma-based OC MDM studies, including testing of pre-diagnostic specimens, are warranted.
•Whole methylome sequencing identified novel ovarian cancer methylated DNA markers.•An 11-MDM ovarian cancer panel discriminated between ovarian cancer and no cancer in plasma.•In plasma, the 11-MDM panel identified all 5 early-stage high grade serous ovarian cancers.
Alterations in DNA methylation are early events in endometrial cancer (EC) development and may have utility in EC detection via tampon-collected vaginal fluid.
For discovery, DNA from frozen EC, ...benign endometrium (BE), and benign cervicovaginal (BCV) tissues underwent reduced representation bisulfite sequencing (RRBS) to identify differentially methylated regions (DMRs). Candidate DMRs were selected based on receiver operating characteristic (ROC) discrimination, methylation level fold-change between cancers and controls, and absence of background CpG methylation. Methylated DNA marker (MDM) validation was performed using qMSP on DNA from independent EC and BE FFPE tissue sets. Women ≥45 years of age with abnormal uterine bleeding (AUB) or postmenopausal bleeding (PMB) or any age with biopsy-proven EC self-collected vaginal fluid using a tampon prior to clinically indicated endometrial sampling or hysterectomy. Vaginal fluid DNA was assayed by qMSP for EC-associated MDMs. Random forest modeling analysis was performed to generate predictive probability of underlying disease; results were 500-fold in-silico cross-validated.
Thirty-three candidate MDMs met performance criteria in tissue. For the tampon pilot, 100 EC cases were frequency matched by menopausal status and tampon collection date to 92 BE controls. A 28-MDM panel highly discriminated between EC and BE (96% (95%CI 89–99%) specificity; 76% (66–84%) sensitivity (AUC 0.88). In PBS/EDTA tampon buffer, the panel yielded 96% (95% CI 87–99%) specificity and 82% (70–91%) sensitivity (AUC 0.91).
Next generation methylome sequencing, stringent filtering criteria, and independent validation yielded excellent candidate MDMs for EC. EC-associated MDMs performed with promisingly high sensitivity and specificity in tampon-collected vaginal fluid; PBS-based tampon buffer with added EDTA improved sensitivity. Larger tampon-based EC MDM testing studies are warranted.
•Whole methylome sequencing identified novel endometrial cancer (EC) methylated DNA markers (MDMs).•A 28-MDM EC panel discriminated between EC and benign endometrium in vaginal fluid collected by tampons.•An abbreviated 3-MDM EC panel performed with similar sensitivity and specificity as the 28-MDM panel.
Introduction: Non-invasive assays are needed to better discriminate patients with prostate cancer (PCa) to avoid over-treatment of indolent disease. We analyzed 14 methylated DNA markers (MDMs) from ...urine samples of patients with biopsy-proven PCa relative to healthy controls and further studied discrimination of clinically significant PCa (csPCa) from healthy controls and Gleason 6 cancers. Methods: To evaluate the panel, urine from 24 healthy male volunteers with no clinical suspicion for PCa and 24 men with biopsy-confirmed disease across all Gleason scores was collected. Blinded to clinical status, DNA from the supernatant was analyzed for methylation signal within specific DNA sequences across 14 genes (HES5, ZNF655, ITPRIPL1, MAX.chr3.6187, SLCO3A1, CHST11, SERPINB9, WNT3A, KCNB2, GAS6, AKR1B1, MAX.chr3.8028, GRASP, ST6GALNAC2) by target enrichment long-probe quantitative-amplified signal assays. Results: Utilizing an overall specificity cut-off of 100% for discriminating normal controls from PCa cases across the MDM panel resulted in 71% sensitivity (95% CI: 49–87%) for PCa detection (4/7 Gleason 6, 8/12 Gleason 7, 5/5 Gleason 8+) and 76% (50–92%) for csPCa (Gleason ≥ 7). At 100% specificity for controls and Gleason 6 patients combined, MDM panel sensitivity was 59% (33–81%) for csPCa (5/12 Gleason 7, 5/5 Gleason 8+). Conclusions: MDMs assayed in urine offer high sensitivity and specificity for detection of clinically significant prostate cancer. Prospective evaluation is necessary to estimate discrimination of patients as first-line screening and as an adjunct to prostate-specific antigen (PSA) testing.
Lynch syndrome (LS) markedly increases risks of colorectal and endometrial cancers. Early detection biomarkers for LS cancers could reduce the needs for invasive screening and surgical prophylaxis.To ...validate a panel of methylated DNA markers (MDM) previously identified in sporadic colorectal cancer and endometrial cancer for discrimination of these cancers in LS.In a case-control design, previously identified MDMs for the detection of colorectal cancer and endometrial cancer were assayed by qMSP on tissue-extracted DNA. Results were normalized to ACTB values within each sample. Least absolute shrinkage and selection operator models to classify colorectal cancer and endometrial cancer were trained on sporadic cases and controls and then applied to classify colorectal cancer and endometrial cancer, in those with LS, and cross-validated.We identified colorectal cancer cases (23 with LS, 48 sporadic), colorectal controls (32 LS, 48 sporadic), endometrial cancer cases (30 LS, 48 sporadic), and endometrial controls (29 LS, 37 sporadic). A 3-MDM panel (LASS4, LRRC4, and PPP2R5C) classified LS-CRC from LS controls with an AUC of 0.92 (0.84-0.99); results were similar for sporadic colorectal cancer. A 6-MDM panel (SFMBT2, MPZ, CYTH2, DIDO1, chr10.4479, and EMX2OS) discriminated LS-EC from LS controls with an AUC of 0.92 (0.83-1.0); the AUC for sporadic endometrial cancer versus sporadic controls was nominally higher, 0.99 (0.96-1.0).MDMs previously identified in sporadic endometrial cancer and colorectal cancer discriminate between endometrial cancer and benign endometrium and colorectal cancer and benign colorectum in LS. This supports the inclusion of patients with LS within future prospective clinical trials evaluating endometrial cancer and colorectal cancer MDMs and may provide a new avenue for cancer screening or surveillance in this high-risk population.
Lynch syndrome (LS) markedly increases risks of colorectal and endometrial cancers. Early detection biomarkers for LS cancers could reduce the needs for invasive screening and surgery. Methylated DNA markers previously identified in sporadic endometrial cancer and colorectal cancer discriminate between benign and cancer tissue in LS.
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