Label-free digital pathology using infrared (IR) imaging with subsequent proteomic analysis for bladder cancer (BC) has revealed the first protein biomarker (AHNAK2) for BC.

AHNAK2 differentiates between chronic cystitis and a non-muscle invasive-type BC, which is challenging to diagnose. A report (“Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer”) in the American Journal of Pathology describes this new diagnostic procedure, which is label-free, automated, observer-independent, and as sensitive and specific as established histopathological methods.

New Diagnostic Technique image
Label-free Fourier transform infrared (FTIR) imaging (left) classifies the unaltered tissue thin section (red: tumor, cyan: connective tissue, blue: muscle). This information is then used to cut out tissue samples of the same kind with laser capture microdissection (middle). The tissue samples are then analyzed with proteomics to identify new protein biomarkers for diagnostics. [American Journal of Pathology]

“Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections,” wrote the investigators.

“Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography–tandem mass spectrometry–based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.”

Distinguishing benign inflammatory conditions in the bladder from low-grade and advanced cancers can be difficult, especially since some BC treatments induce inflammation, noted the scientists.

“We developed this label-free digital pathology annotation system by IR imaging to support the pathologist, similar to driver assistance in cars. This technique in combination with a proteomics approach allowed us to identify AHNAK2 as an important new biomarker for BC, and the results encourage us to transfer this label-free digital technique to other pathologies,” explained Klaus Gerwert, PhD, chairman of the department of biophysics and the PURE (Protein Research Unit Ruhr within Europe) consortium at Ruhr University Bochum, Germany.

Using label-free Fourier transform IR (FTIR) imaging, investigators were able to classify unaltered tissue thin sections by color to identify regions of interest. “The resulting index color images automates tissue classification, including cancer type, subtype, tissue type, inflammation status, and even tumor grading,” noted Gerwert.

In an analysis of 103 freshly-frozen samples that included confirmed diagnoses for 41 cystitis, 19 low-grade carcinoma, and 43 high-grade carcinoma, FTIR imaging showed a specificity of 95%, sensitivity of 95%, and an accuracy of 95% compared to stained images reviewed by a trained pathologist. The technique also differentiated cancerous from healthy tissue as well as low- from high-grade carcinoma.

Laser capture microdissection was then used to obtain homogenous tissue samples for protein analysis by proteomics. By comparing tissue from patients with inflammatory bladder (cystitis) to samples from patients with invasive, high-grade urothelial carcinoma, the investigators identified three potential biomarkers, with the protein AHNAK2 found to be the best performing candidate biomarker.

In a large cohort that included 310 freshly-frozen, paraffin-embedded tissue samples (51 high-grade cancers, 67 carcinoma in situ [CIS], 84 low-grade cancers, and 108 patients with severe cystitis), AHNAK2 measurement achieved 97% sensitivity and 69% specificity in differentiating between severe cystitis with reactive urothelial atypia (RUA) vs CIS. It also displayed high sensitivity in distinguishing low versus invasive high grades and low grades vs CIS.

“In our study, AHNAK2 was identified and verified in two steps as a candidate biomarker for BC,” said Barbara Sitek, PhD, deputy director, Medizinisches Proteom-Center (MPC), Ruhr University. “AHNAK2 has already been proposed as a potential prognostic biomarker for clear renal cell and pancreatic cancers and is part of a urinary mRNA panel for the diagnosis of BC and prediction of tumor aggressiveness.”

The investigators believe AHNAK2 could be a very helpful tool for detecting CIS recurrence or persistence, particularly because misdiagnosis of CIS can delay treatment of an aggressive malignancy or could lead to unnecessary treatment or bladder removal.

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