Metastatic Carcinomatosis Cirrhosis: A Rare Pattern of Metastasis

Knouse, Phillip; Hancock, Christie; Iwaz, Suzanne; Kaiser, P.

doi:10.7759/cureus.3876

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…Our literature review suggests that extensive liver involvement is sometimes seen in breast cancer patients after prolonged intervals without overt disease progression. Subtle signs of liver involvement may include weight changes, subclinical bleeding from varices, slow accumulation of ascites, jaundice, and even slowly progressive hepatic encephalopathy [13, 20]. In retrospect, there is suspicion that our case of occult liver infiltration may have developed subtly over 6-12 months with the only indicator being subtle increases in bilirubin and alkaline phosphatase values to less than one time the upper limit of normal.…”

Section: Discussionmentioning

confidence: 99%

Radiographically Occult Carcinomatous Spread of Breast Cancer to the Liver: A Challenging Case

Millard

Gupta

Brenin

et al. 2019

Case Reports in Oncological Medicine

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Metastatic carcinomatosis to the liver is a pattern of malignant infiltration that tends to provoke hepatic fibrosis. It is a rare complication of multiple solid tumor types and often seen in the absence of discrete tumor mass in the liver. We report a case of a 69-year-old woman with metastatic ductal carcinoma of the breast who presented with rising serum tumor markers and mildly cirrhotic contour of the liver on a CT scan. An early diagnosis of occult spread to the liver was made by means of a percutaneous liver biopsy showing desmoplastic response to invasive breast cancer cells found diffusely in the liver. This case highlights a rare pattern of metastatic spread of breast cancer as well as predisposing and prognostic features.

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Section: Discussionmentioning

confidence: 99%

Radiographically Occult Carcinomatous Spread of Breast Cancer to the Liver: A Challenging Case

Millard

Gupta

Brenin

et al. 2019

Case Reports in Oncological Medicine

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“…Beyond this, Dermatomyositis (Luu et al, 2015), Rheumatoid Arthritis (Racanelli et al, 2008), and Autoimmune Diseases (Milkiewicz et al, 1999) are recognized paraneoplastic syndromes, which are symptoms that occur at sites distant from a tumor or its metastasis site (Pelosof and Gerber, 2010). In addition, several of our differentially expressed genes, including HLA-DMA, SOCS1, HLA-C, CTNNB1, KRAS, MET, and CD244, are associated with Liver Cirrhosis (Knouse et al, 2019), CD79A, HLA-DMA, SOCS1, HLA-B, HLA-C, IFI35, CD68, MET, PTHLH, CD244, and C2 with Rheumatoid Arthritis (Roy et al, 2011), HLA-B, HPRT1, and C2 with dermatomyositis (Bonnetblanc et al, 1990), and RB1, HLA-DMA, CXCR4, and CTGF with Cirrhosis (Shah and Casciola-Rosen, 2015). We also have several genes, including FTO, HLA-DMA, GAP43, SCN8A, HLA-C, CD68, and CDR2, associated with Multiple Sclerosis (Plantone et al, 2015), which suggest Multiple Sclerosis and Cirrhosis may possibly be a paraneoplastic syndrome that arises with metastasis.…”

Section: Figurementioning

confidence: 99%

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Albaradei

Albaradei²,

Alsaedi³

et al. 2022

Front. Mol. Biosci.

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Deep learning has massive potential in predicting phenotype from different omics profiles. However, deep neural networks are viewed as black boxes, providing predictions without explanation. Therefore, the requirements for these models to become interpretable are increasing, especially in the medical field. Here we propose a computational framework that takes the gene expression profile of any primary cancer sample and predicts whether patients’ samples are primary (localized) or metastasized to the brain, bone, lung, or liver based on deep learning architecture. Specifically, we first constructed an AutoEncoder framework to learn the non-linear relationship between genes, and then DeepLIFT was applied to calculate genes’ importance scores. Next, to mine the top essential genes that can distinguish the primary and metastasized tumors, we iteratively added ten top-ranked genes based upon their importance score to train a DNN model. Then we trained a final multi-class DNN that uses the output from the previous part as an input and predicts whether samples are primary or metastasized to the brain, bone, lung, or liver. The prediction performances ranged from AUC of 0.93–0.82. We further designed the model’s workflow to provide a second functionality beyond metastasis site prediction, i.e., to identify the biological functions that the DL model uses to perform the prediction. To our knowledge, this is the first multi-class DNN model developed for the generic prediction of metastasis to various sites.

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“…The same phenomenon of cirrhosis-like morphologic changes in metastatic liver disease has been described using different terminologies in subsequent decades. “Metastatic carcinomatous liver cirrhosis” was first used in the 1950s [ 10 – 13 ]. The term “pseudocirrhosis” was used in the 1920s–1950s in reference to cirrhotic-like changes arising secondary to pericarditis or tuberculous disease [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Pseudocirrhosis: A Case Series with Clinical and Radiographic Correlation and Review of the Literature

Sadlik,

Anderson,

Lei

et al. 2024

Dig Dis Sci

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Background and aims Pseudocirrhosis is a poorly understood acquired morphologic change of the liver that occurs in the setting of metastatic malignancy and radiographically resembles cirrhosis. Pseudocirrhosis has been primarily described in metastatic breast carcinoma, with few case reports arising from other primary malignancies. We present 29 cases of pseudocirrhosis, including several cases from primary malignancies not previously described. Methods Radiologic, clinical, demographic, and biomedical data were collected retrospectively and analyzed. We compared clinical and radiologic characteristics and outcomes between patients with pseudocirrhosis arising in metastatic breast cancer and non-breast primary malignancies. Results Among the 29 patients, 14 had breast cancer and 15 had non-breast primaries including previously never reported primaries associated with pseudocirrhosis, melanoma, renal cell carcinoma, appendiceal carcinoid, and cholangiocarcinoma. Median time from cancer diagnosis to development of pseudocirrhosis was 80.8 months for patients with primary breast cancer and 29.8 months for non-breast primary ( p = 0.02). Among all patients, 15 (52%) had radiographic features of portal hypertension. Radiographic evidence of portal hypertension was identified in 28.6% of breast cancer patients, compared to 73.3% of those with non-breast malignancies ( p = 0.03). Conclusion Pseudocirrhosis has most commonly been described in the setting of metastatic breast cancer but occurs in any metastatic disease to the liver. Our study suggests that portal hypertensive complications are more common in the setting of non-breast primary cancers than in metastatic breast cancer. Prior exposure to multiple chemotherapeutic agents, and agents known to cause sinusoidal injury, is a common feature but not essential for the development of pseudocirrhosis.

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Metastatic Carcinomatosis Cirrhosis: A Rare Pattern of Metastasis

Cited by 5 publications

References 10 publications

Radiographically Occult Carcinomatous Spread of Breast Cancer to the Liver: A Challenging Case

Radiographically Occult Carcinomatous Spread of Breast Cancer to the Liver: A Challenging Case

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Pseudocirrhosis: A Case Series with Clinical and Radiographic Correlation and Review of the Literature

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