A Danish national effort of <i>BRCA1/2</i> variant classification

A Danish national effort of <i>BRCA1/2</i> variant classificatio

Hypermethylated DNA, a circulating biomarker for colorectal cancer detection

<div><p>Background</p><p>Colorectal cancer (CRC) is one of the most common cancers in the western world. Screening is an efficient method of reducing cancer-related mortality. Molecular biomarkers for cancer in general and CRC in particular have been proposed, and hypermethylated DNA from stool or blood samples are already implemented as biomarkers for CRC screening.</p><p>We aimed to evaluate the performance of proven hypermethylated DNA promoter regions as plasma based biomarkers for CRC detection.</p><p>Methods</p><p>We conducted a cross-sectional case-control study of 193 CRC patients and 102 colonoscopy-verified healthy controls. Using methylation specific polymerase chain reaction, we evaluated 30 DNA promoter regions previously found to be CRC specific. We used multivariable logistic regression with stepwise backwards selection, and subsequent <i>leave-pair-out cross validation</i>, to calculate the optimism corrected area under the receiver operating characteristics curve (AUC) for all stage as well as early stage CRC.</p><p>Results</p><p>None of the individual DNA promoter regions provided an overall sensitivity above 30% at a reasonable specificity. However, seven hypermethylated promoter regions (<i>ALX4</i>, <i>BMP3</i>, <i>NPTX2</i>, <i>RARB</i>, <i>SDC2</i>, <i>SEPT9</i>, and <i>VIM</i>) along with the covariates sex and age yielded an optimism corrected AUC of 0.86 for all stage CRC and 0.85 for early stage CRC. Overall sensitivity for CRC detection was 90.7% at 72.5% specificity using a cut point value of 0.5.</p><p>Conclusions</p><p>Individual hypermethylated DNA promoter regions have limited value as CRC screening markers. However, a panel of seven hypermethylated promoter regions show great promise as a model for CRC detection.</p></div

Stepwise backwards selection according to model number.

<p>Note. Logistic regression modelling with stepwise backwards selection. Potential predictor variables are located in the top row. Model number is recorded in the left column. Area under the receiver operating curve (AUC) according to model number and the P-value according to the removed predictor variable is located in the two rightward columns.</p

Patient characteristics.

<p>Patient characteristics.</p

Model 12s sensitivity, specificity, PPV, and NPV for CRC.

<p>Model 12s sensitivity, specificity, PPV, and NPV for CRC.</p

Receiver operating characteristics curves for colorectal cancer.

<p>Note. A) ROC curve for all stage CRC with a non-optimism corrected AUC of 0.8870. B) ROC curve for stage I and II CRC with a non-optimism corrected AUC of 0.8775. Receiver operating characteristics (ROC). Colorectal cancer (CRC). Area under the receiver operating characteristics curve (AUC).</p

Number of methylated promoter regions according to patient group.

<p>Number of methylated promoter regions according to patient group.</p

Hypermethylation status according to gene names.

<p>Hypermethylation status according to gene names.</p

Feasibility and early clinical impact of precision medicine for late-stage cancer patients in a regional public academic hospital

Our goal was to describe a precision medicine program in a regional academic hospital, characterize features of included patients and present early data on clinical impact. We prospectively included 163 eligible patients with late-stage cancer of any diagnosis from June 2020 to May 2022 in the Proseq Cancer trial. Molecular profiling of new or fresh frozen tumor biopsies was done by WES and RNAseq with parallel sequencing of non-tumoral DNA as individual reference. Cases were presented at a National Molecular Tumor Board (NMTB) for discussion of targeted treatment. Subsequently, patients were followed for at least 7 months. 80% (N = 131) of patients had a successful analysis done, disclosing at least one pathogenic or likely pathogenic variant in 96%. A strongly or potentially druggable variant was found in 19% and 73% of patients, respectively. A germline variant was identified in 2.5%. Median time from trial inclusion to NMTB decision was one month. One third (N = 44) of patients who underwent molecularly profiling were matched with a targeted treatment, however, only 16% were either treated (N = 16) or are waiting for treatment (N = 5), deteriorating performance status being the primary cause of failure. A history of cancer among 1st degree relatives, and a diagnosis of lung or prostate cancer correlated with greater chance of targeted treatment being available. The response rate of targeted treatments was 40%, the clinical benefit rate 53%, and the median time on treatment was 3.8 months. 23% of patients presented at NMTB were recommended clinical trial participation, not dependent on biomarkers. Precision medicine in end-stage cancer patients is feasible in a regional academic hospital but should continue within the frame of clinical protocols as few patients benefit. Close collaboration with comprehensive cancer centers ensures expert evaluations and equality in access to early clinical trials and modern treatment.</p