Jeffrey E. Gershenwald

A false-negative diagnosis of cancer can lead to a delay in effective treatment and a poorer prognosis. Here, we use the example of cutaneous melanoma to examine how many years of life are lost after a false-negative diagnosis compared to a primarily correct diagnosis. From 1996 to 2015, 9,063 patients are prospectively registered in the German Central Malignant Melanoma Registry and followed up until December 2023. A false-negative diagnosis is found in 206 (2.3%) patients. The median time to correct diagnosis is 24.0 months. The 10-year recurrence-free survival probabilities are 32.9% for false-negative diagnoses and 76.2% for correct diagnoses (p < 0.001). The 10-year melanoma-specific survival probabilities are 62.1% versus 85.0% (p < 0.001). On average, each person with an initial false-negative diagnosis loses 8.2 years of life compared to people with a correct diagnosis. This high number of years of life lost raises the question of whether similar results also apply to other types of cancer.

Body mass index values by patient ID for all RNASeq cohorts.

Supplementary Table 1: Baseline characteristics for patients included in the integrated gene set enrichment analysis (Figure 2-3) by cohort; Supplementary Table 6: The most frequent somatic alterations (alts) in patients with regionally metastatic melanoma by body mass index from The Cancer Genome Atlas cohort; Supplemental Table 7: Integrated gene set enrichment analysis for pathways associated with fatty acid metabolism by body mass index; Supplemental Table 8: Gene expression of selected genes of interest involved in fatty acid metabolism.

Beta-diversity analysis stratified by sex based on Bray-Curtis dissimilarity represents microbiome samples with metastatic melanoma in terms of the two top principal components (explaining around 17% of variance) obtained from the principal coordinate analysis. Red dots are from overweight/obese (OW/OB) BMI patients, and blue dots are from normal (NL) BMI patients. Shading inside the dots indicates the female gender. This is a subgroup analysis of Figure 5B.

Immune cell analysis by BMI. A. Immunohistochemistry (IHC) analysis for CD8-, CD45RO-, FOXP3-, CD68-, GZMB-, PD-1-, LAG-3-, and CD3-positive cells in overweight/obese (OW/OB) verse normal (NL) tumors as defined by body mass index from the MD Anderson Cancer Center (MDA) cohort. Line represents median +/- interquartile range; each dot represents a single tumor. B. IHC analysis for PD-L1-, CD45RO-, FOXP3-, EOMES-, GZMB-, PD-1-, TBET-, and TBET:FOXP3-positive cells in OW/OB verse NL tumors as defined by body mass index from the Gide cohort. Line represents median +/- interquartile range; each dot represents a single tumor.

Integrated gene set enrichment analysis of subgroups by body mass index BMI. This figure compares gene expression between overweight/obese (OW/OB) and normal (NL) BMI patients with metastatic melanoma across subgroups by sex, cohort, and tissue site. Supplementary Figure 2 presents a dotplot of genes differentially up- or downregulated in OW/OB patients versus NL BMI patients by subgroups. Red indicates upregulation in OW/OB verse NL.

Immune cell analysis by BMI and sex. A. Immunohistochemistry (IHC) analysis of the MDA cohort stratified by BMI and sex. Line represents median +/- interquartile range; each dot represents a single tumor. B. IHC analysis of the Gide cohort stratified by BMI and sex. Line represents median +/- interquartile range; each dot represents a single tumor.

Differential gene expression analysis for each subgroup.

Differential gene expression analysis for covariates controlled.

RNASeq data for the MDA cohort (n=61) with associated clinical info.