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CANCER LIVER CANCER Show tissue menu
BREAST CANCER CARCINOID CERVICAL CANCER COLORECTAL CANCER ENDOMETRIAL CANCER GLIOMA HEAD AND NECK CANCER LIVER CANCER LUNG CANCER LYMPHOMA
MELANOMA OVARIAN CANCER PANCREATIC CANCER PROSTATE CANCER RENAL CANCER SKIN CANCER STOMACH CANCER TESTIS CANCER THYROID CANCER UROTHELIAL CANCER
LIHC TCGA LIHC VALIDATION PROTEIN LIHC CPTAC PROTEIN EXPRESSION
ANTIBODIES
AND
VALIDATION
Dictionary
Liver cancer
Human cancer
Liver hepatocellular carcinoma
LIVER HEPATOCELLULAR CARCINOMA (TCGA) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA (VALIDATION) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA - Protein relative expression (CPTAC)
Number of samples 330
Samples
Sample ID Sample type nRPX
571 Tumor 2.9
357 Tumor 2.9
953 Tumor 2.6
627 Tumor 2.5
361 Tumor 2.5
423 Tumor 2.5
697 Tumor 2.4
713 Tumor 2.3
465 Tumor 2.3
411 Tumor 1.8
128 Normal 1.7
923 Tumor 1.7
393 Tumor 1.6
513 Tumor 1.4
722 Normal 1.4
491 Tumor 1.2
914 Normal 1.1
313 Tumor 1.1
426 Normal 1.1
616 Normal 1.0
148 Normal 1.0
227 Tumor 0.9
298 Normal 0.9
278 Normal 0.9
981 Tumor 0.8
648 Normal 0.8
344 Normal 0.8
138 Normal 0.8
628 Normal 0.8
472 Normal 0.7
944 Normal 0.7
114 Normal 0.7
258 Normal 0.7
355 Tumor 0.7
328 Normal 0.7
137 Tumor 0.7
746 Normal 0.7
1014 Normal 0.7
924 Normal 0.7
132 Normal 0.6
615 Tumor 0.6
642 Normal 0.6
695 Tumor 0.6
568 Normal 0.6
824 Normal 0.6
698 Normal 0.6
388 Normal 0.6
868 Normal 0.5
1028 Normal 0.5
136 Normal 0.5
456 Normal 0.5
546 Normal 0.5
214 Normal 0.5
755 Tumor 0.5
366 Normal 0.5
1022 Normal 0.5
1032 Normal 0.5
564 Normal 0.5
362 Normal 0.4
428 Normal 0.4
867 Tumor 0.4
462 Normal 0.4
534 Normal 0.4
487 Tumor 0.4
474 Normal 0.4
1045 Tumor 0.4
365 Tumor 0.4
172 Normal 0.3
466 Normal 0.3
364 Normal 0.3
816 Normal 0.3
786 Normal 0.3
464 Normal 0.3
228 Normal 0.3
618 Normal 0.3
954 Normal 0.3
968 Normal 0.3
232 Normal 0.2
728 Normal 0.2
257 Tumor 0.2
915 Tumor 0.2
268 Normal 0.2
356 Normal 0.2
436 Normal 0.2
572 Normal 0.1
358 Normal 0.1
864 Normal 0.1
448 Normal 0.1
468 Normal 0.1
714 Normal 0.1
396 Normal 0.1
481 Tumor 0.1
222 Normal 0.1
445 Tumor 0.1
882 Normal 0.1
518 Normal 0.1
422 Normal 0.0
484 Normal 0.0
412 Normal 0.0
444 Normal 0.0
982 Normal 0.0
647 Tumor 0.0
482 Normal 0.0
1046 Normal 0.0
352 Normal 0.0
1042 Normal 0.0
314 Normal 0.0
1044 Normal -0.1
533 Tumor -0.1
363 Tumor -0.1
424 Normal -0.1
866 Normal -0.1
716 Normal -0.1
976 Normal -0.1
721 Tumor -0.1
686 Normal -0.1
911 Tumor -0.1
141 Tumor -0.1
196 Normal -0.1
574 Normal -0.1
473 Tumor -0.1
874 Normal -0.2
912 Normal -0.2
818 Normal -0.2
162 Normal -0.2
557 Tumor -0.2
967 Tumor -0.2
1027 Tumor -0.2
142 Normal -0.2
353 Tumor -0.2
414 Normal -0.2
312 Normal -0.2
666 Normal -0.2
558 Normal -0.3
272 Normal -0.3
492 Normal -0.3
342 Normal -0.3
664 Normal -0.3
376 Normal -0.3
354 Normal -0.3
922 Normal -0.3
538 Normal -0.3
416 Normal -0.3
126 Normal -0.3
984 Normal -0.3
212 Normal -0.3
332 Normal -0.3
218 Normal -0.3
916 Normal -0.3
498 Normal -0.3
862 Normal -0.4
636 Normal -0.4
386 Normal -0.4
434 Normal -0.4
956 Normal -0.4
878 Normal -0.4
756 Normal -0.4
483 Tumor -0.4
488 Normal -0.4
964 Normal -0.4
858 Normal -0.4
432 Normal -0.4
111 Normal -0.4
526 Normal -0.4
188 Normal -0.5
528 Normal -0.5
1013 Tumor -0.5
852 Normal -0.5
446 Normal -0.5
368 Normal -0.5
494 Normal -0.5
327 Tumor -0.5
525 Tumor -0.5
926 Normal -0.5
286 Normal -0.5
394 Normal -0.5
778 Normal -0.5
738 Normal -0.5
478 Normal -0.6
554 Normal -0.6
861 Tumor -0.6
952 Normal -0.6
884 Normal -0.6
873 Tumor -0.6
192 Normal -0.6
161 Tumor -0.6
277 Tumor -0.6
514 Normal -0.6
186 Normal -0.6
1016 Normal -0.7
1043 Tumor -0.7
957 Tumor -0.7
146 Normal -0.7
723 Tumor -0.7
221 Tumor -0.7
696 Normal -0.7
685 Tumor -0.7
461 Tumor -0.7
421 Tumor -0.7
452 Normal -0.7
662 Normal -0.7
384 Normal -0.7
978 Normal -0.7
918 Normal -0.7
451 Tumor -0.8
224 Normal -0.8
1026 Normal -0.8
958 Normal -0.8
672 Normal -0.8
284 Normal -0.8
195 Tumor -0.8
823 Tumor -0.9
563 Tumor -0.9
523 Tumor -0.9
536 Normal -0.9
211 Tumor -0.9
443 Tumor -0.9
635 Tumor -0.9
938 Normal -1.0
567 Tumor -1.0
742 Normal -1.0
343 Tumor -1.0
415 Tumor -1.0
262 Normal -1.0
127 Tumor -1.0
1041 Tumor -1.0
341 Tumor -1.1
217 Tumor -1.1
524 Normal -1.1
311 Tumor -1.1
427 Tumor -1.1
392 Normal -1.1
375 Tumor -1.2
966 Normal -1.2
223 Tumor -1.2
493 Tumor -1.2
413 Tumor -1.2
516 Normal -1.2
963 Tumor -1.2
351 Tumor -1.2
145 Tumor -1.3
112 Tumor -1.3
425 Tumor -1.3
857 Tumor -1.3
617 Tumor -1.3
187 Tumor -1.3
383 Tumor -1.3
641 Tumor -1.4
447 Tumor -1.4
267 Tumor -1.4
863 Tumor -1.4
124 Normal -1.4
213 Tumor -1.4
125 Tumor -1.4
943 Tumor -1.4
535 Tumor -1.4
431 Tumor -1.4
573 Tumor -1.4
135 Tumor -1.4
123 Tumor -1.4
191 Tumor -1.4
391 Tumor -1.5
744 Normal -1.5
331 Tumor -1.5
917 Tumor -1.5
185 Tumor -1.5
497 Tumor -1.5
231 Tumor -1.5
261 Tumor -1.5
463 Tumor -1.5
297 Tumor -1.5
285 Tumor -1.5
715 Tumor -1.6
745 Tumor -1.6
387 Tumor -1.6
433 Tumor -1.6
467 Tumor -1.7
283 Tumor -1.7
977 Tumor -1.7
455 Tumor -1.7
671 Tumor -1.7
553 Tumor -1.7
131 Tumor -1.7
777 Tumor -1.7
113 Tumor -1.8
517 Tumor -1.8
367 Tumor -1.8
951 Tumor -1.8
955 Tumor -1.8
663 Tumor -1.9
814 Normal -1.9
271 Tumor -1.9
147 Tumor -1.9
395 Tumor -1.9
877 Tumor -1.9
537 Tumor -2.0
785 Tumor -2.0
921 Tumor -2.0
527 Tumor -2.0
171 Tumor -2.0
515 Tumor -2.0
545 Tumor -2.0
865 Tumor -2.0
471 Tumor -2.0
743 Tumor -2.1
881 Tumor -2.1
477 Tumor -2.1
975 Tumor -2.1
913 Tumor -2.1
1021 Tumor -2.2
1031 Tumor -2.2
1015 Tumor -2.2
1025 Tumor -2.2
925 Tumor -2.2
817 Tumor -2.2
815 Tumor -2.2
435 Tumor -2.2
813 Tumor -2.2
937 Tumor -2.2
665 Tumor -2.3
851 Tumor -2.3
883 Tumor -2.3
385 Tumor -2.3
741 Tumor -2.4
965 Tumor -2.4
983 Tumor -2.5
661 Tumor -2.5
727 Tumor -2.6
737 Tumor -2.6
724 Normal -3.4
Show allShow less
LIVER CANCER - Protein expressioni

A mouse-over function shows sample information and annotation data. Click on an image to view it in a full screen mode. Samples can be filtered based on level of antibody staining by selecting one or several of the following categories: high, medium, low and not detected. The assay and annotation is described here.

Note that samples used for immunohistochemistry by the Human Protein Atlas do not correspond to samples in the TCGA dataset.

 

Antibody stainingi

Antibody staining in the annotated cell types in the current human tissue is reported as not detected, low, medium, or high, based on conventional immunohistochemistry profiling in selected tissues. This score is based on the combination of the staining intensity and fraction of stained cells.

Each image is clickable and will lead to virtual microscopy that enables deeper exploration of all samples and also displays staining intensity scores, fraction scores and subcellular localization as well as patient and tissue information for each sample.


Antibody HPA020361
 Staining
  High
  Medium
  Low
  Not detected
 Intensity
  Strong
  Moderate
  Weak
  Negative
 Quantity
  >75%
  75%-25%
  <25%
  None
 Location
  Nuclear
  Cytoplasmic/membranous
  Cytoplasmic/membranous,nuclear
  None
Cholangiocarcinoma
Carcinoma, Hepatocellular, NOS

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