Many studies have used histomorphological features to more precisely predict the prognosis of patients with colon cancer, focusing on tumor budding, poorly differentiated clusters, and the tumor–stroma ratio. Here, we introduce SARIFA: Stroma AReactive Invasion Front Area(s). We defined SARIFA as the direct contact between a tumor gland/tumor cell cluster (≥5 cells) and inconspicuous surrounding adipose tissue in the invasion front. In this retrospective, single-center study, we classified 449 adipose-infiltrative adenocarcinomas (not otherwise specified) from two groups based on SARIFA and found 25% of all tumors to be SARIFA-positive. Kappa values between the two pathologists were good/very good: 0.77 and 0.87. Patients with SARIFA-positive tumors had a significantly shorter colon-cancer-specific survival (p = 0.008, group A), absence of metastasis, and overall survival (p < 0.001, p = 0.003, group B). SARIFA was significantly associated with adverse features such as pT4 stage, lymph node metastasis, tumor budding, and higher tumor grade. Moreover, SARIFA was confirmed as an independent prognostic indicator for colon-cancer-specific survival (p = 0.011, group A). SARIFA assessment was very quick (<1 min). Because of low interobserver variability and good prognostic significance, SARIFA seems to be a promising histomorphological prognostic indicator in adipose-infiltrative adenocarcinomas of the colon. Further studies should validate our results and also determine whether SARIFA is a universal prognostic indicator in solid cancers.

In this study, we developed the Binary ImaGe Colon Metastasis classifier (BIg-CoMet), a semi-guided approach for the stratification of colon cancer patients into two risk groups for the occurrence of distant metastasis, using an InceptionResNetV2-based deep learning model trained on binary images. We enrolled 291 colon cancer patients with pT3 and pT4 adenocarcinomas and converted one cytokeratin-stained representative tumor section per case into a binary image. Image augmentation and dropout layers were incorporated to avoid overfitting. In a validation collective (n = 128), BIg-CoMet was able to discriminate well between patients with and without metastasis (AUC: 0.842, 95% CI: 0.774–0.911). Further, the Kaplan–Meier curves of the metastasis-free survival showed a highly significant worse clinical course for the high-risk group (log-rank test: p < 0.001), and we demonstrated superiority over other established risk factors. A multivariable Cox regression analysis adjusted for confounders supported the use of risk groups as a prognostic factor for the occurrence of metastasis (hazard ratio (HR): 5.4, 95% CI: 2.5–11.7, p < 0.001). BIg-CoMet achieved good performance for both UICC subgroups, especially for UICC III (n = 53), with a positive predictive value of 80%. Our study demonstrates the ability to stratify colon cancer patients via a semi-guided process on images that primarily reflect tumor architecture.

Dermoscopy adds important information to the assessment of cutaneous melanoma, but the risk of progression is predicted by histologic parameters and therefore requires surgery and histopathologic preparation. Neo-vascularization is crucial for tumor progression and worsens prognosis. The aim of this study was the in vivo evaluation of blood vessel patterns in melanoma with dynamic optical coherence tomography (D-OCT) and the correlation with dermoscopic and histologic malignancy parameters for the risk assessment of melanoma. In D-OCT vessel patterns, shape, distribution and presence/type of branching of 49 melanomas were evaluated in vivo at three depths and correlated with the same patterns in dermoscopy and with histologic parameters after excision. In D-OCT, blood vessel density and atypical shapes (coils and serpiginous vessels) increased with higher tumor stage. The histologic parameters ulceration and Hmb45- and Ki67-positivity increased, whereas regression, inflammation and PD-L1-positivity decreased with risk. CD31, VEGF and Podoplanin correlated with D-OCT vasculature findings. B-RAF mutation status had no influence. Due to pigment overlay and the summation effect, the vessel evaluation in dermoscopy and D-OCT did not correlate well. In summary, atypical vessel patterns in melanoma correlate with histologic parameters for risk for metastases. Tumor vasculature can be noninvasively assessed using D-OCT before surgery.

UICC stage IV small-cell lung cancer (SCLC) is a highly aggressive malignancy without curative treatment options. Several randomized trials have demonstrated improved survival rates through the addition of checkpoint inhibitors to first-line platin-based chemotherapy. Consequently, a combination of chemo- and immunotherapy has become standard palliative treatment. However, no reliable predictive biomarkers for treatment response exist. Neither PD-L1 expression nor tumor mutational burden have proven to be effective predictive biomarkers. In this study, we compared the cellular immune statuses of SCLC patients to a healthy control cohort and investigated changes in peripheral blood B, T, and NK lymphocytes, as well as several of their respective subsets, during treatment with immunochemotherapy (ICT) using flow cytometry. Our findings revealed a significant decrease in B cells, while T cells showed a trend to increase throughout ICT. Notably, high levels of exhausted CD4+ and CD8+ cells, alongside NK subsets, increased significantly during treatment. Furthermore, we correlated decreases/increases in subsets after two cycles of ICT with survival. Specifically, a decrease in Th17 cells indicated a better overall survival. Based on these findings, we suggest conducting further investigation into Th17 cells as a potential early predictive biomarkers for response in patients receiving palliative ICT for stage IV SCLC.

To date, therapeutic responses in plaque psoriasis are evaluated with clinical scores. No objective examination has been established. A recently developed non-invasive imaging tool, line-field confocal optical coherence tomography (LC-OCT), enables the in vivo live imaging of skin changes in psoriasis under therapy. The aim of this study was to measure therapeutic response clinically and with LC-OCT, comparing the subjectively scored epidermal changes with an AI-supported analysis. This prospective, observational study included 12 patients with psoriasis starting a systemic treatment with IL-17 inhibitors (secukinumab, ixekizumab, and bimekizumab). LC-OCT and clinical assessment with a local psoriasis and severity index of the study plaque and a control area were performed before the initiation of therapy as well as after 4 and 12 weeks of treatment. A manual and AI-supported measurement of the thickness of epidermis, stratum corneum, and undulation of the dermo-epidermal junction was carried out. Acanthosis and hyperkeratosis showed a significant reduction under treatment. AI-supported calculations were compared to subjective measurements showing good reliability with high correlation. AI-supported analysis of vascular changes may serve as a prognostic and therapeutic response marker in the future.

Background: mTOR-Is positively influence the occurrence and course of certain tumors after solid organ transplantation. mTOR-inhibitor (mTOR-I) treatment, either alone or in combination with Calcineurininhibitors (CNIs), significantly reduces the incidence of malignancies after organ transplantation. However, there is no information on which mTOR-I, Sirolimus (SIR) or Everolimus (ERL), has a stronger anti-tumoral effect. Methods: The current literature was searched for prospective randomized controlled trials in renal transplantation. There were 1.164 trials screened, of which 20 could be included (7465 patients). We performed a network meta-analysis to analyze the relative risk of different types of mTOR-I compared to CNI treatment on malignancies after transplantation. A minimum follow-up of 24 months was mandatory for inclusion. Results: Four different types of mTOR-I treatment were analyzed in network meta-analyses—SIR mono, ERL mono, SIR with CNI, and ERL with CNI. The average follow-up of all trials was 43.8 months. All four different mTOR-I regimes showed a significant reduced relative risk for malignancies compared to a regular CNI-treatment with the strongest effect under SIR in combination with a CNI (RR 0.23, CI 0.09–0.55, p = 0.001). This effect remained consistent for all tumor entities except non-melanoma skin cancer (RR 0.25, CI 0.07–0.90, p = 0.033). Conclusions: It is well known that an mTOR-I based treatment in transplant patients reduces the risk of tumor manifestation in comparison to CNI treatment. A combination of SIR and CNI seems to be the most potent mTOR-I therapy against malignancies.