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Background: The advances in deep learning-based pathological image analysis have invoked tremendous insights into cancer prognostication. Still, lack of interpretability remains a significant barrier to clinical application. Methods: We established an integrative prognostic neural network for intrahepatic cholangiocarcinoma (iCCA), towards a comprehensive evaluation of both architectural and fine-grained information from whole-slide images. Then, leveraging on multi-modal data, we conducted extensive interrogative approaches to the models, to extract and visualize the morphological features that most correlated with clinical outcome and underlying molecular alterations. Results: The models were developed and optimized on 373 iCCA patients from our center and demonstrated consistent accuracy and robustness on both internal (n = 213) and external (n = 168) cohorts. The occlusion sensitivity map revealed that the distribution of tertiary lymphoid structures, the geometric traits of the invasive margin, the relative composition of tumor parenchyma and stroma, the extent of necrosis, the presence of the disseminated foci, and the tumor-adjacent micro-vessels were the determining architectural features that impacted on prognosis. Quantifiable morphological vector extracted by CellProfiler demonstrated that tumor nuclei from high-risk patients exhibited significant larger size, more distorted shape, with less prominent nuclear envelope and textural contrast. The multi-omics data (n = 187) further revealed key molecular alterations left morphological imprints that could be attended by the network, including glycolysis, hypoxia, apical junction, mTORC1 signaling, and immune infiltration. Conclusions: We proposed an interpretable deep-learning framework to gain insights into the biological behavior of iCCA. Most of the significant morphological prognosticators perceived by the network are comprehensible to human minds. [ABSTRACT FROM AUTHOR]

The prognostic value and clinical relevance of tertiary lymphoid structures (TLSs) in intrahepatic cholangiocarcinoma (iCCA) remain unclear. Thus, we aimed to investigate the prognostic value and functional involvement of TLSs in iCCA. We retrospectively included 962 patients from 3 cancer centers across China. The TLSs at different anatomic subregions were quantified and correlated with overall survival (OS) by Cox regression and Kaplan-Meier analyses. Multiplex immunohistochemistry (mIHC) was applied to characterize the composition of TLSs in 39 iCCA samples. A quaternary TLS scoring system was established for the intra-tumor region (T score) and peri-tumor region (P score) respectively. T scores positively correlated with favorable prognosis (p < 0.001), whereas a high P score signified worse survival (p < 0.001). mIHC demonstrated that both T follicular helper and regulatory T cells were significantly increased in intra-tumoral TLSs compared to peri-tumoral counterparts (p < 0.05), and regulatory T cell frequencies within intra-tumoral TLSs were positively associated with P score (p < 0.05) rather than T score. Collectively, the combination of T and P scores stratified iCCAs into 4 immune classes with distinct prognoses (p < 0.001) that differed in the abundance and distribution pattern of TLSs. Patients displaying an immune-active pattern had the lowest risk, with 5-year OS rates of 68.8%, whereas only 3.4% of patients with an immune-excluded pattern survived at 5 years (p < 0.001). The C-index of the immune class was statistically higher than the TNM staging system (0.73 vs. 0.63, p < 0.001). These results were validated in an internal and 2 external cohorts. The spatial distribution and abundance of TLSs significantly correlated with prognosis and provided a useful immune classification for iCCA. T follicular helper and regulatory T cells may play a critical role in determining the functional orientation of spatially different TLSs. Tertiary lymphoid structures (TLSs) are associated with favorable prognosis in a number of cancers. However, their role in intrahepatic cholangiocarcinoma (iCCA) remains unclear. Herein, we comprehensively evaluated the spatial distribution, abundance, and cellular composition of TLSs in iCCA, and revealed the opposite prognostic impacts of TLSs located within or outside the tumor. This difference could be mediated by the different immune cell subsets present within the spatially distinct TLSs. Based on our analysis, we were able to stratify iCCAs into 4 immune subclasses associated with varying prognoses. [Display omitted] • Tertiary lymphoid structures (TLSs) within and outside the tumor have opposite prognostic impacts on patients with iCCA. • The heterogeneous distribution of Tfh and Treg cells within distinct TLSs might be a determinant of their functional state. • The geographic integration of TLSs stratified iCCAs into 4 immune subclasses with distinct clinical outcomes. [ABSTRACT FROM AUTHOR]