Automatic analysis of nuclear features reveals a non-tumoral predictor of tumor grade in bladder cancer.

BACKGROUND & OBJECTIVES: Tumor grade determines prognosis in urothelial carcinoma. The classification of low and high grade is based on nuclear morphological features that include nuclear size, hyperchromasia and pleomorphism. These features are subjectively assessed by the pathologists and are not numerically measured, which leads to high rates of interobserver variability. The purpose of this study is to assess the value of a computer-based image analysis tool for identifying predictors of tumor grade in bladder cancer. METHODS: Four hundred images of urothelial tumors were graded by five pathologists and two expert genitourinary pathologists using a scale of 1 (lowest grade) to 5 (highest grade). A computer algorithm was used to automatically segment the nuclei and to provide morphometric parameters for each nucleus, which were used to establish the grading algorithm. Grading algorithm was compared to pathologists' agreement. RESULTS: Comparison of the grading scores of the five pathologists with the expert genitourinary pathologists score showed agreement rates between 88.5% and 97.5%.The agreement rate between the two expert genitourinary pathologists was 99.5%. The quantified algorithm based conventional parameters that determine the grade (nuclear size, pleomorphism and hyperchromasia) showed > 85% agreement with the expert genitourinary pathologists. Surprisingly, the parameter that was most associated with tumor grade was the 10th percentile of the nuclear area, and high grade was associated with lower 10th percentile nuclei, caused by the presence of more inflammatory cells in the high-grade tumors. CONCLUSION: Quantitative nuclear features could be applied to determine urothelial carcinoma grade and explore new biologically explainable parameters with better correlation to grade than those currently used.

Mutated TP53 in Circulating Tumor DNA as a Risk Level Biomarker in Head and Neck Squamous Cell Carcinoma Patients.

Circulating tumor DNA (ctDNA) has been suggested as a surrogate biomarker for early detection of cancer recurrence. We aimed to explore the utility of ctDNA as a noninvasive prognostic biomarker in newly diagnosed head and neck squamous cell carcinoma (HNSCC) patients. Seventy HNSCC specimens were analysed for the detection of TP53 genetic alterations utilizing next-generation sequencing (NGS). TP53 mutations were revealed in 55 (79%). Upon detection of a significant TP53 mutation, circulating cell-free DNA was scrutinized for the presence of the tumor-specific mutation. ctDNA was identified at a minimal allele frequency of 0.08% in 21 out of 30 processed plasma samples. Detectable ctDNA correlated with regional spread (N stage ≥ 1, p = 0.011) and poorer 5-year progression-free survival (20%, 95% CI 10.9 to 28.9, p = 0.034). The high-risk worst pattern of invasion (WPOI grade 4-5) and deep invasion were frequently found in patients whose ctDNA was detected (p = 0.087 and p = 0.072, respectively). Detecting mutated TP53 ctDNA was associated with poor progression-free survival and regional metastases, indicating its potential role as a prognostic biomarker. However, ctDNA detectability in early-stage disease and the mechanisms modulating its release into the bloodstream must be further elucidated.

Perineural invasion detection in pancreatic ductal adenocarcinoma using artificial intelligence.

Perineural invasion (PNI) refers to the presence of cancer cells around or within nerves, raising the risk of residual tumor. Linked to worse prognosis in pancreatic ductal adenocarcinoma (PDAC), PNI is also being explored as a therapeutic target. The purpose of this work was to build a PNI detection algorithm to enhance accuracy and efficiency in identifying PNI in PDAC specimens. Training used 260 manually segmented nerve and tumor HD images from 6 scanned PDAC cases; Analytical performance analysis used 168 additional images; clinical analysis used 59 PDAC cases. The algorithm pinpointed key areas of tumor-nerve proximity for pathologist confirmation. Analytical performance reached sensitivity of 88% and 54%, and specificity of 78% and 85% for the detection of nerve and tumor, respectively. Incorporating tumor-nerve distance in clinical evaluation raised PNI detection from 52 to 81% of all cases. Interestingly, pathologist analysis required an average of only 24 s per case. This time-efficient tool accurately identifies PNI in PDAC, even with a small training cohort, by imitating pathologist thought processes.

Neoadjuvant Osimertinib Followed by Sequential Definitive Radiation Therapy and/or Surgery in Stage III Epidermal Growth Factor Receptor-Mutant Non-Small Cell Lung Cancer: An Open-Label, Single-Arm, Phase 2 Study.

PURPOSE: The treatment for unresectable, locally advanced stage III non-small cell lung cancer (NSCLC) is concurrent chemoradiation therapy (CRT) followed by consolidation durvalumab. This study aimed to evaluate the benefit of neoadjuvant osimertinib as an alternative therapy to this approach with the aim of reducing the radiation field. METHODS AND MATERIALS: This investigation was a nonrandomized, open-label, single-arm, phase 2, prospective, proof-of-concept study. Eligible patients were classified as having treatment-naïve, nonoperable, stage III epidermal growth factor receptor-mutant NSCLC. Patients received 80 mg of oral osimertinib daily for 12 weeks before definitive radiation therapy (RT) and/or surgery. The response was assessed at weeks 6 and 12. For responders, sequential definitive RT and/or surgery were planned. Nonresponders were started on standard CRT. After RT ± surgery or CRT, patients were followed for 2 years without adjuvant therapy. The primary endpoint was the objective response rate (ORR), with September 20, 2022, set as the cut-off for data collection. Secondary endpoints were safety and the gross tumor volume (GTV), planned tumor volume (PTV), and the percentage of total lung volume minus GTV exceeding 20 Gy (V20%) before versus after osimertinib. Exploratory analyses included assessments of the presence of plasma circulating tumor-free DNA (ctDNA) before osimertinib treatment, at weeks 6 and 12, at the end of RT, and 6 weeks post-RT. RESULTS: Twenty-four patients were included (19 women; median age, 73 years; range, 51-82 years). Nineteen of 24 had never smoked, 20 of 24 had adenocarcinoma, 16 of 24 had exon 19 deletions, and 8 of 24 had exon 21 mutations. Participants had stage IIIA (10), IIIB (9), or IIIC (5) disease. Three patients were excluded from the analysis (1 dropped out and 2 were still undergoing osimertinib treatment at the cut-off date). The ORR to induction osimertinib was 95.2% (17 partial response, 3 complete response, and 1 progressive disease). After induction osimertinib, 13 of 20 patients were definitively radiated, 3 of 20 underwent surgery, and 5 of 20 were excluded. Four patients were restaged as stage IV (contralateral ground-glass opacities responded to osimertinib), and 1 patient withdrew informed consent. Three patients underwent surgery, one of whom was treated with RT. Two patients achieved pT1aN0, and one achieved pathologic complete response. The median GTV, PTV, and V20% before osimertinib treatment were 47.4 ± 76.9 cm3 (13.5-234.9), 227.0 ± 258.8 cm3 (77.8-929.2), and 27.1 ± 16.4% (6.2-60.3), respectively. The values after osimertinib treatment were 27.5 ± 42.3 cm3 (2.99-137.7; -48 ± 20%; P = .02), 181.9 ±198.4 cm3 (54-718.1; -31 ± 20%; P = .01), and 21.8 ± 11.7% (9.1-44.15; -24 ± 40%; P = .04), respectively. PTV/GTV/V20% reduction was associated with tumor size and central location. The median follow-up time was 28.71 months (range, 0.4-45.1 months), and median disease-free survival was not reached (mean, 30.59; standard error, 3.94; 95% confidence interval, 22.86-38.31). ctDNA was detected in 5 patients; 4 of 5 were positive for ctDNA at baseline and became negative during osimertinib induction but were again positive after osimertinib treatment was terminated. Interestingly, 3 patients who were ctDNA negative at baseline became weakly positive after RT and then were negative at follow-up. No significant adverse events were reported during the osimertinib or radiation phases. CONCLUSIONS: Neoadjuvant osimertinib therapy is feasible in patients with stage III lung cancer NSCLC, followed by definitive radiation and/or surgery, with an ORR of 95.2% and an excellent safety profile. Osimertinib induction for 12 weeks before definitive radiation (chemo-free) significantly reduced the radiation field by nearly 50% with a linear association with tumor size. Further studies are needed to test this chemo-free approach for long-term outcomes before practices are changed.

Digital PCR-Based Method for Detecting CDKN2A Loss in Brain Tumours.

INTRODUCTION: CDKN2A is a key tumour suppressor gene and loss of CDKN2A can be found in many tumours. In astrocytoma grade IV, CDKN2A is deleted in more than 50% of tumours. In many instances, low-grade gliomas with homozygous loss of CDKN2A behave like high grade tumours. The available techniques for CDKN2A loss are laborious, expensive, unreliable, or unavailable in most pathology institutes. Therefore, although it is essential for accurate brain tumour diagnosis, the routine diagnosis does not include testing for CDKN2A deletion. METHODS: We developed a digital polymerase chain reaction (dPCR) assay for CDKN2A loss detection. The assay is based on counting the copy number of CDKN2A gene and of a reference gene on the same chromosome. It was tested for the detection limit with regard to tumour content and minimal DNA quantity. It was then tested on 24 clinical samples with known CDKN2A status. Additionally, we tested 44 gliomas with unknown CDKN2A status. RESULTS: We found that the newly developed assay is reliable in tissue with more than 50% tumour content and more than 0.4 ng of DNA. The validation cohort showed complete concordance, and we were able to detect homozygous loss in 16 gliomas with unknown CDKN2A status. DISCUSSION: The method presented can give a fast, cost-effective, clinically reliable evaluation of CDKN2A loss in tissue with more than 50% tumour content. Its ability to work with old samples and with low amounts of DNA makes it the favoured assay in cases where other techniques fail.

Spatial organization and early signaling of the B-cell receptor in CLL.

Most chronic lymphocytic leukemia (CLL) clones express B-cell receptors (BcR) of both IgM/IgD isotypes; however, 5%-10% of CLL cases express isotype-switched immunoglobulin G (IgG). The early signaling and spatial patterning of the various BcRs at steady state and after activation are still fully unresolved. Herein, we show higher expression of the BcR signalosome elements and a more robust constitutive cell-intrinsic proximal BcR signaling in CLL with unmutated IGHV expressing IgM isotype (IgM U-CLL), compared with IGHV-mutated CLL (M-CLL) expressing either IgM or IgG isotypes. IgM in U-CLL is frequently located in the membrane plane in polarized patches, occasionally in caps, and sometimes inside the cells. Among M-CLL, IgM is scattered laterally in the membrane plane in a similar pattern as seen in normal B cells, whereas IgG is dispersed around the cell membrane in smaller clusters than in IgM U-CLL. Upon BcR engagement, both IgG and IgM expressing M-CLL showed attenuated signaling and only slight spatial reorganization dynamics of BcR microclusters and internalization, compared with the extensive reorganization and internalization of the BcR in IgM expressing U-CLL. The global gene signature of IgG M-CLL was closely related to that of IgM M-CLL rather than IgM U-CLL. Overall, we report fundamental differences in the basal composition, biochemical status, and spatial organization of the BcR in the three examined immunogenetic CLL subtypes that correlate with their clinical behavior. On the basis of our findings, IgG class-switched M-CLL likely represents the same disease as IgM M-CLL rather than a different biological and/or clinical entity.

The risk of PD-L1 expression misclassification in triple-negative breast cancer.

PURPOSE: Stratification of patients with triple-negative breast cancer (TNBC) for anti-PD-L1 therapy is based on PD-L1 expression in tumor biopsies. This study sought to evaluate the risk of PD-L1 misclassification. METHODS: We conducted a high-resolution analysis on ten surgical specimens of TNBC. First, we determined PD-L1 expression pattern distribution via manual segmentation and measurement of 6666 microscopic clusters of positive PD-L1 immunohistochemical staining. Then, based on these results, we generated a computer model to calculate the effect of the positive PD-L1 fraction, aggregate size, and distribution of PD-L1 positive cells on the diagnostic accuracy. RESULTS: Our computer-based model showed that larger aggregates of PD-L1 positive cells and smaller biopsy size were associated with higher fraction of false results (P < 0.001, P < 0.001, respectively). Additionally, our model showed a significant increase in error rate when the fraction of PD-L1 expression was close to the cut-off (error rate of 12.1%, 0.84%, and 0.65% for PD-L1 positivity of 0.5-1.5%, ≤ 0.5% ,and ≥ 1.5%, respectively, P < 0.0001). Interestingly, false positive results were significantly higher than false negative results (0.51-22.62%, with an average of 6.31% versus 0.11-11.36% with an average of 1.58% for false positive and false negative results, respectively, P < 0.05). Furthermore, heterogeneous tumors with different aggregate sizes in the same tumor, were associated with increased rate of false results in comparison to homogenous tumors (P < 0.001). CONCLUSION: Our model can be used to estimate the risk of PD-L1 misclassification in biopsies, with potential implications for treatment decisions.

Metastasis-Entrained Eosinophils Enhance Lymphocyte-Mediated Antitumor Immunity.

The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein-coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ-activated eosinophils facilitated CD4+ and CD8+ T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics. SIGNIFICANCE: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.

Extracellular Vesicle-Derived DNA vs. CfDNA as a Biomarker for the Detection of Colon Cancer.

Liquid biopsy has emerged as a promising non-invasive way to diagnose tumor and monitor its progression. Different types of liquid biopsies have different advantages and limitations. In the present research, we compared the use of two types of liquid biopsy, extracellular vesicle-derived DNA (EV-DNA) and cell-free DNA (cfDNA) for identifying tumor mutations in patients with colon carcinoma. METHOD: DNA was extracted from the tumor tissue of 33 patients diagnosed with colon carcinoma. Targeted NGS panel, based on the hotspots panel, was used to identify tumor mutations. Pre-surgery serum and plasma were taken from the patients in which mutation was found in the tumor tissue. Extracellular vesicles were isolated from the serum followed by the extraction of EV-DNA. CfDNA was extracted from the plasma. The mutations found in the tumor were used to detect the circulating tumor DNA using ultra-deep sequencing. We compared the sensitivity of mutation detection and allele frequency obtained in EV-DNA and cfDNA. RESULTS: The sensitivity of mutation detection in EV-DNA and cfDNA was 61.90% and 66.67%, respectively. We obtained almost identical sensitivity of mutation detection in EV-DNA and cfDNA in each of the four stages of colon carcinoma. The total DNA concentration and number mutant copies were higher in cfDNA vs. EV-DNA (p value = 0.002 and 0.003, respectively). CONCLUSION: Both cfDNA and EV-DNA can serve as tumor biomarkers. The use of EV-DNA did not lead to improved sensitivity or better detection of tumor DNA in the circulation.

Local sharing as a predominant determinant of synaptic matrix molecular dynamics.

Recent studies suggest that central nervous system synapses can persist for weeks, months, perhaps lifetimes, yet little is known as to how synapses maintain their structural and functional characteristics for so long. As a step toward a better understanding of synaptic maintenance we examined the loss, redistribution, reincorporation, and replenishment dynamics of Synapsin I and ProSAP2/Shank3, prominent presynaptic and postsynaptic matrix molecules, respectively. Fluorescence recovery after photobleaching and photoactivation experiments revealed that both molecules are continuously lost from, redistributed among, and reincorporated into synaptic structures at time-scales of minutes to hours. Exchange rates were not affected by inhibiting protein synthesis or proteasome-mediated protein degradation, were accelerated by stimulation, and greatly exceeded rates of replenishment from somatic sources. These findings indicate that the dynamics of key synaptic matrix molecules may be dominated by local protein exchange and redistribution, whereas protein synthesis and degradation serve to maintain and regulate the sizes of local, shared pools of these proteins.