Redefinition of tumor capsule: Rho-dependent clustering of cancer-associated fibroblasts in favor of tensional homeostasis

Establishment of nomogram prediction model of contrast-enhanced ultrasound and Gd-EOB-DTPA-enhanced MRI for vessels encapsulating tumor clusters pattern of hepatocellular carcinoma

To establish clinical prediction models of vessels encapsulating tumor clusters (VETC) pattern using preoperative contrast-enhanced ultrasound (CEUS) and gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI) in patients with hepatocellular carcinoma (HCC). A total of 111 resected HCC lesions from 101 patients were included. Preoperative imaging features of CEUS and EOB-MRI, postoperative recurrence, and survival information were collected from medical records. The best subset regression and multivariable Cox regression were used to select variables to establish the prediction model. The VETC-positive group had a statistically lower survival rate than the VETC-negative group. The selected variables were peritumoral enhancement in the arterial phase (AP), hepatobiliary phase (HBP) on EOB-MRI, intratumoral branching enhancement in the AP of CEUS, intratumoral hypoenhancement in the portal phase of CEUS, incomplete capsule, and tumor size. A nomogram was developed. High and low nomogram scores with a cutoff value of 168 points showed different recurrence-free survival rates and overall survival rates. The area under the curve (AUC) and accuracy were 0.804 and 0.820, respectively, indicating good discrimination. Decision curve analysis showed a good clinical net benefit (threshold probability > 5%), while the Hosmer-Lemeshow test yielded excellent calibration (P = 0.6759). The AUC of the nomogram model combining EOB-MRI and CEUS was higher than that of the models with EOB-MRI factors only (0.767) and CEUS factors only (0.7). The nomogram verified by bootstrapping showed AUC and calibration curves similar to those of the nomogram model. The Prediction model based on CEUS and EOB-MRI is effective for preoperative noninvasive diagnosis of VETC.

A Therapeutic DNA Vaccine Targeting HPV16 E7 in Combination with Anti-PD-1/PD-L1 Enhanced Tumor Regression and Cytotoxic Immune Responses

Persistent infection of high-risk human papillomavirus (HPV) and the expression of E6 and E7 oncoproteins are the main causes of cervical cancer. Several prophylactic HPV vaccines are used in the clinic, but these vaccines have limited efficacy in patients already infected with HPV. Since HPV E7 is vital for tumor-specific immunity, developing a vaccine against HPV E7 is an attractive strategy for cervical cancer treatment. Here, we constructed an HPV16 E7 mutant that loses the ability to bind pRb while still eliciting a robust immune response. In order to build a therapeutic DNA vaccine, the E7 mutant was packaged in an adenovirus vector (Ad-E7) for efficient expression and enhanced immunogenicity of the vaccine. Our results showed that the Ad-E7 vaccine effectively inhibited tumor growth and increased the proportion of interferon-gamma (IFN-γ)-secreting CD8+ T cells in the spleen, and tumor-infiltrating lymphocytes in a mouse cervical cancer model was achieved by injecting with HPV16-E6/E7-expressing TC-1 cells subcutaneously. Combining the Ad-E7 vaccine with the PD-1/PD-L1 antibody blockade significantly improved the control of TC-1 tumors. Combination therapy elicited stronger cytotoxic T lymphocyte (CTL) responses, and IFN-γ secretion downregulated the proportion of Tregs and MDSCs significantly. The expressions of cancer-promoting factors, such as TNF-α, were also significantly down-regulated in the case of combination therapy. In addition, combination therapy inhibited the number of capillaries in tumor tissues and increased the thickness of the tumor capsule. Thus, Ad-E7 vaccination, in combination with an immune checkpoint blockade, may benefit patients with HPV16-associated cervical cancer.

SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics

Recent advancements in spatial transcriptomic technologies have enabled the measurement of whole transcriptome profiles with preserved spatial context. However, limited by spatial resolution, the measured expressions at each spot are often from a mixture of multiple cells. Computational deconvolution methods designed for spatial transcriptomic data rarely make use of the valuable spatial information as well as the neighboring similarity information. Here, we propose SONAR, a Spatially weighted pOissoN-gAmma Regression model for cell-type deconvolution with spatial transcriptomic data. SONAR directly models the raw counts of spatial transcriptomic data and applies a geographically weighted regression framework that incorporates neighboring information to enhance local estimation of regional cell type composition. In addition, SONAR applies an additional elastic weighting step to adaptively filter dissimilar neighbors, which effectively prevents the introduction of local estimation bias in transition regions with sharp boundaries. We demonstrate the performance of SONAR over other state-of-the-art methods on synthetic data with various spatial patterns. We find that SONAR can accurately map region-specific cell types in real spatial transcriptomic data including mouse brain, human heart and human pancreatic ductal adenocarcinoma. We further show that SONAR can reveal the detailed distributions and fine-grained co-localization of immune cells within the microenvironment at the tumor-normal tissue margin in human liver cancer.

An invasive zone in human liver cancer identified by Stereo-seq promotes hepatocyte-tumor cell crosstalk, local immunosuppression and tumor progression

Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as "the invasive zone". We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs' overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n = 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.

Histopathological Investigation of Meningioma Capsule with Respect to Tumor Cell Invasion

No previous study has histopathologically investigated whether a meningioma capsule presents with tumor cells. We investigated which types of tumor capsules (TCs) included tumor cells to help intraoperatively determine those TCs that do not need to be removed and have a low recurrence risk. We investigated 22 specimens of 14 newly diagnosed meningiomas from February 2011 to June 2021. The capsules were classified into three types: TC, capsule-like thickened arachnoid membrane (CAM), and extended membrane (EM). Capsule properties were scored by hardness (soft = 1, medium = 2, hard = 3) and transparency (high = 1, medium = 2, low = 3). The hardness, transparency, and score sums were compared between capsules with and without tumor invasion in the CAM and EM types. The mean follow-up duration was 40.6 months, and there was only one recurrence in a remote location from the residual capsule. Nine capsules were classified as TC, seven as CAM, and six as EM. The tumor cells invaded 88.9% of TCs, 42.9% of CAMs, and 50% of EMs. The hardness, transparency, and score sums for CAMs with tumor invasion were lower than those for CAMs without tumor invasion, although not significant (P = 0.114, P = 0.114, P = 0.057, respectively). A thickened TC or soft and highly transparent CAM indicated a high risk for tumor cell invasion; thus, such cases require a careful and long-term follow-up. Hard and low transparent residual CAMs may have had a low risk for tumor invasion; therefore, leaving such capsules that tightly adhere to the eloquent cortex can be theoretically justified to avoid damaging the brain surface.

Comprehensive analysis of spatial architecture in primary liver cancer

Heterogeneity is the major challenge for cancer prevention and therapy. Here, we first constructed high-resolution spatial transcriptomes of primary liver cancers (PLCs) containing 84,823 spots within 21 tissues from seven patients. The progressive comparison of spatial tumor microenvironment (TME) characteristics from nontumor to leading-edge to tumor regions revealed that the tumor capsule potentially affects intratumor spatial cluster continuity, transcriptome diversity, and immune cell infiltration. Locally, we found that the bidirectional ligand-receptor interactions at the 100-μm-wide cluster-cluster boundary contribute to maintaining intratumor architecture and the PROM1⁺ and CD47⁺ cancer stem cell niches are related to TME remodeling and tumor metastasis. Last, we proposed a TLS-50 signature to accurately locate tertiary lymphoid structures (TLSs) spatially and unveiled that the distinct composition of TLSs is shaped by their distance to tumor cells. Our study provides previous unknown insights into the diverse tumor ecosystem of PLCs and has potential benefits for cancer intervention.