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  • STRUCT & INT

  • PRRC2B
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
967 Tumor 1.1
965 Tumor 1.1
865 Tumor 1.0
285 Tumor 0.9
131 Tumor 0.9
943 Tumor 0.9
743 Tumor 0.9
957 Tumor 0.9
1021 Tumor 0.8
567 Tumor 0.8
533 Tumor 0.8
367 Tumor 0.8
537 Tumor 0.8
937 Tumor 0.7
395 Tumor 0.7
497 Tumor 0.7
535 Tumor 0.7
777 Tumor 0.7
851 Tumor 0.7
523 Tumor 0.7
913 Tumor 0.6
647 Tumor 0.6
861 Tumor 0.6
983 Tumor 0.6
727 Tumor 0.6
471 Tumor 0.6
557 Tumor 0.6
661 Tumor 0.6
815 Tumor 0.5
545 Tumor 0.5
663 Tumor 0.5
955 Tumor 0.5
573 Tumor 0.5
953 Tumor 0.5
1013 Tumor 0.5
327 Tumor 0.5
671 Tumor 0.5
921 Tumor 0.5
391 Tumor 0.5
737 Tumor 0.5
1015 Tumor 0.5
351 Tumor 0.5
1041 Tumor 0.5
695 Tumor 0.5
665 Tumor 0.4
697 Tumor 0.4
923 Tumor 0.4
447 Tumor 0.4
413 Tumor 0.4
393 Tumor 0.4
915 Tumor 0.4
487 Tumor 0.4
493 Tumor 0.4
863 Tumor 0.4
571 Tumor 0.4
1031 Tumor 0.4
473 Tumor 0.4
425 Tumor 0.4
981 Tumor 0.4
355 Tumor 0.4
515 Tumor 0.4
527 Tumor 0.3
857 Tumor 0.3
365 Tumor 0.3
411 Tumor 0.3
267 Tumor 0.3
641 Tumor 0.3
977 Tumor 0.3
283 Tumor 0.3
1025 Tumor 0.3
817 Tumor 0.3
617 Tumor 0.3
517 Tumor 0.3
123 Tumor 0.3
125 Tumor 0.3
311 Tumor 0.3
951 Tumor 0.3
978 Normal 0.3
685 Tumor 0.3
385 Tumor 0.3
135 Tumor 0.3
171 Tumor 0.3
881 Tumor 0.3
461 Tumor 0.3
331 Tumor 0.3
1043 Tumor 0.3
715 Tumor 0.3
724 Normal 0.3
113 Tumor 0.3
963 Tumor 0.3
297 Tumor 0.3
145 Tumor 0.3
525 Tumor 0.2
313 Tumor 0.2
536 Normal 0.2
968 Normal 0.2
553 Tumor 0.2
975 Tumor 0.2
427 Tumor 0.2
498 Normal 0.2
1014 Normal 0.2
223 Tumor 0.2
187 Tumor 0.2
627 Tumor 0.2
261 Tumor 0.2
721 Tumor 0.2
191 Tumor 0.2
474 Normal 0.2
477 Tumor 0.2
1016 Normal 0.2
147 Tumor 0.2
383 Tumor 0.2
883 Tumor 0.2
361 Tumor 0.2
483 Tumor 0.2
864 Normal 0.2
554 Normal 0.2
745 Tumor 0.2
524 Normal 0.2
1028 Normal 0.2
911 Tumor 0.2
982 Normal 0.2
884 Normal 0.2
375 Tumor 0.1
563 Tumor 0.1
448 Normal 0.1
221 Tumor 0.1
357 Tumor 0.1
714 Normal 0.1
472 Normal 0.1
161 Tumor 0.1
852 Normal 0.1
1042 Normal 0.1
1026 Normal 0.1
574 Normal 0.1
918 Normal 0.1
814 Normal 0.1
958 Normal 0.1
1046 Normal 0.1
572 Normal 0.1
277 Tumor 0.1
227 Tumor 0.1
416 Normal 0.1
1044 Normal 0.1
868 Normal 0.1
195 Tumor 0.1
412 Normal 0.1
866 Normal 0.1
127 Tumor 0.1
518 Normal 0.1
984 Normal 0.1
755 Tumor 0.1
141 Tumor 0.1
286 Normal 0.1
467 Tumor 0.1
534 Normal 0.1
213 Tumor 0.1
938 Normal 0.1
463 Tumor 0.1
917 Tumor 0.1
363 Tumor 0.1
698 Normal 0.1
966 Normal 0.1
558 Normal 0.1
257 Tumor 0.1
228 Normal 0.1
435 Tumor 0.1
952 Normal 0.1
451 Tumor 0.1
615 Tumor 0.1
224 Normal 0.1
528 Normal 0.1
862 Normal 0.1
564 Normal 0.0
916 Normal 0.0
482 Normal 0.0
353 Tumor 0.0
491 Tumor 0.0
713 Tumor 0.0
284 Normal 0.0
956 Normal 0.0
858 Normal 0.0
628 Normal 0.0
912 Normal 0.0
464 Normal 0.0
696 Normal 0.0
964 Normal 0.0
1045 Tumor 0.0
823 Tumor 0.0
481 Tumor 0.0
867 Tumor 0.0
484 Normal 0.0
455 Tumor 0.0
231 Tumor 0.0
816 Normal 0.0
976 Normal 0.0
785 Tumor 0.0
1022 Normal 0.0
494 Normal 0.0
328 Normal 0.0
462 Normal 0.0
786 Normal 0.0
488 Normal 0.0
364 Normal 0.0
728 Normal 0.0
433 Tumor 0.0
716 Normal 0.0
211 Tumor 0.0
136 Normal 0.0
914 Normal 0.0
443 Tumor 0.0
478 Normal 0.0
824 Normal 0.0
137 Tumor 0.0
271 Tumor 0.0
546 Normal 0.0
1032 Normal 0.0
648 Normal 0.0
882 Normal 0.0
873 Tumor 0.0
368 Normal 0.0
341 Tumor -0.1
568 Normal -0.1
664 Normal -0.1
387 Tumor -0.1
112 Tumor -0.1
874 Normal -0.1
376 Normal -0.1
538 Normal -0.1
926 Normal -0.1
312 Normal -0.1
422 Normal -0.1
922 Normal -0.1
813 Tumor -0.1
944 Normal -0.1
384 Normal -0.1
778 Normal -0.1
444 Normal -0.1
492 Normal -0.1
278 Normal -0.1
662 Normal -0.1
516 Normal -0.1
925 Tumor -0.1
672 Normal -0.1
616 Normal -0.1
878 Normal -0.1
513 Tumor -0.1
415 Tumor -0.1
217 Tumor -0.1
298 Normal -0.1
954 Normal -0.1
362 Normal -0.1
421 Tumor -0.1
636 Normal -0.1
723 Tumor -0.1
431 Tumor -0.1
428 Normal -0.1
132 Normal -0.1
526 Normal -0.1
268 Normal -0.1
126 Normal -0.1
738 Normal -0.1
635 Tumor -0.1
666 Normal -0.2
343 Tumor -0.2
924 Normal -0.2
741 Tumor -0.2
396 Normal -0.2
262 Normal -0.2
642 Normal -0.2
742 Normal -0.2
877 Tumor -0.2
514 Normal -0.2
232 Normal -0.2
722 Normal -0.2
212 Normal -0.2
818 Normal -0.2
746 Normal -0.2
142 Normal -0.2
388 Normal -0.2
423 Tumor -0.2
188 Normal -0.2
618 Normal -0.2
436 Normal -0.2
386 Normal -0.2
686 Normal -0.2
426 Normal -0.2
354 Normal -0.2
356 Normal -0.2
392 Normal -0.2
114 Normal -0.2
218 Normal -0.2
465 Tumor -0.2
756 Normal -0.2
272 Normal -0.2
148 Normal -0.2
258 Normal -0.2
314 Normal -0.3
466 Normal -0.3
214 Normal -0.3
366 Normal -0.3
445 Tumor -0.3
456 Normal -0.3
414 Normal -0.3
138 Normal -0.3
192 Normal -0.3
446 Normal -0.3
352 Normal -0.3
468 Normal -0.3
185 Tumor -0.3
424 Normal -0.3
222 Normal -0.3
111 Normal -0.3
186 Normal -0.3
452 Normal -0.3
162 Normal -0.4
124 Normal -0.4
1027 Tumor -0.4
744 Normal -0.4
344 Normal -0.4
172 Normal -0.4
394 Normal -0.4
332 Normal -0.4
196 Normal -0.4
434 Normal -0.4
432 Normal -0.4
146 Normal -0.5
128 Normal -0.5
358 Normal -0.5
342 Normal -0.7
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 HPA021022
 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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The Human Protein Atlas project is funded
by the Knut & Alice Wallenberg Foundation.


contact@proteinatlas.org