Major data analysis errors invalidate cancer microbiome findings.

We re-analyzed the data from a recent large-scale study that reported strong correlations between microbial organisms and 33 different cancer types, and that created machine learning predictors with near-perfect accuracy at distinguishing among cancers. We found at least two fundamental flaws in the reported data and in the methods: (1) errors in the genome database and the associated computational methods led to millions of false positive findings of bacterial reads across all samples, largely because most of the sequences identified as bacteria were instead human; and (2) errors in transformation of the raw data created an artificial signature, even for microbes with no reads detected, tagging each tumor type with a distinct signal that the machine learning programs then used to create an apparently accurate classifier. Each of these problems invalidates the results, leading to the conclusion that the microbiome-based classifiers for identifying cancer presented in the study are entirely wrong. These flaws have subsequently affected more than a dozen additional published studies that used the same data and whose results are likely invalid as well.

Major data analysis errors invalidate cancer microbiome findings.

IMPORTANCE: Recent reports showing that human cancers have a distinctive microbiome have led to a flurry of papers describing microbial signatures of different cancer types. Many of these reports are based on flawed data that, upon re-analysis, completely overturns the original findings. The re-analysis conducted here shows that most of the microbes originally reported as associated with cancer were not present at all in the samples. The original report of a cancer microbiome and more than a dozen follow-up studies are, therefore, likely to be invalid.

Erratum: Tertiary Lymphoid Structures Associate with Tumour Stage in Urothelial Bladder Cancer.

[This corrects the article DOI: 10.3233/BLC-170120.].

Tertiary Lymphoid Structures Associate with Tumour Stage in Urothelial Bladder Cancer.

BACKGROUND: Urothelial bladder cancer (UBC) is a highly prevalent disease in North America, however its optimal management remains elusive. The contribution of B cell associated responses is poorly understood in bladder cancer. Lymphoid neogenesis is a hallmark of an active immune response at tumor sites that sometimes leads to formation of tertiary lymphoid structures (TLS) that resemble germinal centers formed in secondary lymphoid organs. OBJECTIVE: This study was conducted with an aim to investigate the presence and characteristics of TLS in UBC with a focus to compare and contrast the TLS formation in treatment naive low grade non-muscle invasive (NMIBC) and muscle invasive bladder cancers (MIBC). METHODS: The study cohort consisted of transurethral bladder resection tumour (TURBT) specimens from 28 patients. Sections showing lymphoid aggregates in hematoxylin and eosin (H&E) stained TURBT specimens were further subjected to multi-color immunohistochemistry using immune cell markers specific to CD20+ B cells, CD3+ and CD8+ T cells, PNAd+ high endothelial venules, CD208+ mature dendritic cells, CD21+ follicular dendritic cells to confirm the hallmarks of classical germinal centers. RESULTS: Our pilot study investigating the presence of TLS in bladder cancer patients is the first to demonstrate that well-formed TLS are more common in aggressive high grade MIBC tumors compared to low grade NIMBC. CONCLUSIONS: These novel findings suggest B cell mediated anti-tumour humoral immune responses in bladder cancer progression.